Tableau Conference-ish | Opening Keynote Livestream Watchalong 2020

0:00You're live. And we're live. Hello everyone

0:04. TC-ish. I'm being told I'm live. I'm Ravi.

0:09Tim is joining

0:10in a second. Are you there yet, Tim? No.

0:13Nope, he's not. But it's cool. There we go.

0:18And we are actually

0:19live. I can see it. I can see it. So,

0:21fantastic. So thanks everyone for joining.

0:24What we're going to try

0:25and do is watch along. We're going to chat

0:28along the way, myself and Tim. Obviously

0:31chuck in any

0:31comments you have along the way. We'll try

0:33and keep up. There's going to be a bit of

0:35lag, I think, between

0:36what we say and what you see. But yeah,

0:39hopefully it'll be good fun to watch the

0:43keynote. And

0:43then we've got what, 13 minutes left before

0:45it starts. So let's go. Hello Mark. We're

0:50going

0:50through loud and clear. Cool. So there's

0:56going to be about a bit of setup beforehand

1:00because

1:00Tim's doing some magic behind the curtain.

1:03But great, great to see you all and

1:06experiences. The reason

1:07me and Tim came up with this idea, I think,

1:10and I can say this before it turns up, is

1:13really like

1:14in a conference environment, we'd be, I

1:16guess, sitting near each other, at least

1:18texting or whatever,

1:19and keeping in touch, just giving

1:20commentary. This is a unique experience

1:22because you can talk over

1:23it and no one's going to be like, shut up

1:25or whatever behind you. And you can see

1:26like live

1:27reactions and whatnot. Because with these,

1:29typically with these things, there's always

1:31going to be a

1:31bit of like guff, which you're not really

1:33paying attention to. So instead of just

1:35scrolling towards,

1:36you can either hear us chat or in our case,

1:39we can just chat to each other. So great to

1:42see you all.

1:44Let's see, Tim can go. So we're going to, I

1:48've got this stream open on one screen over

1:51here.

1:52I've got Tim in front of me and hey, we've

1:54got, we've now got the stream running

1:56alongside.

1:57Tim, will we have the actual, what's the

1:59word, the audio coming through as well?

2:02Fantastic. So the audio will come through

2:06as well. If you actually do want to listen

2:09to what's

2:10being said, rather than us rambling, we'll

2:12probably recommend having it on in one ear

2:15or something

2:15like that. But the visual will be there and

2:17there will be some audio coming through

2:19while we chat.

2:23So yeah, it's great to have a few of you on

2:25with us. Hello, how are you doing, sir?

2:32Good. Hi, everyone. Hi, you can see I'm

2:35literally live editing the OBS template in

2:38front of me.

2:39I had to wait to have the zoom call up

2:41before we had this going properly. So yeah,

2:45this is a little

2:45bit of real time editing OBS, but we're

2:48going to get there in the end. We also have

2:50a FaceTime call

2:51just off screen. Because yeah, exactly,

2:53exactly. To set this up correctly. It's a

2:57multi device

2:57setup. It's a multi device setup. So how

2:59are you doing, Tim? What's, it's weird. A

3:02year ago, we were

3:02in Vegas. We were actually in Vegas waiting

3:04for a conference. Absolutely. Man, it's

3:07crazy. It's

3:07crazy. Like, but, you know, at the

3:09beginning of this year, I was thinking I

3:11was looking forward

3:13to TC, I think this was supposed to be the

3:14big TC where lots of things were happening

3:16because

3:17of Salesforce. And in the end, obviously,

3:19it's now not a physical conference. So we

3:22lost that

3:22opportunity to talk to people about the

3:24experience. What's it like what the first

3:26year of Salesforce

3:27being, you know, but we're here in the end,

3:30I'm just grateful we have some sort of

3:33resemblance of

3:33conference and people are still sort of

3:35taking it and with all the enthusiasm and

3:37energy. So yeah,

3:38I'm pretty, pretty, pretty chuffed that we

3:40've got something going on. It's possible to

3:42do a live

3:42stream, which is good. So yeah, yeah, it's

3:44exciting. I think the last well, last time

3:46we did

3:46the live stream was live. Well, we recorded

3:49a date and podcast, but had the video going

3:52alongside it.

3:53So that was good fun as well. So yeah,

3:56absolutely. Absolutely. So I'm just going

3:57to turn the browser

3:58down a little bit for everyone. Cool. How's

4:01the audio coming through for you all? Is it

4:03good a

4:04balance between myself, Tim and the audio

4:06and screen? How's it all sound? Just put

4:08something

4:08in the chat and let us know. Yeah, let us

4:09know. I'm just going to open up the screen

4:11myself so I

4:12can listen to my third pair of headphones.

4:14I've actually got AirPods in and actually a

4:19headphone and now I'm like, I need another.

4:22You need just another ear, right? Yeah,

4:25exactly. I

4:26need another ear or I need another person

4:28if I'm listening. A proper producer, right?

4:32A proper

4:32producer, someone behind the curtain. So

4:34how are we far away? We're about 10 minutes

4:36out from the

4:37keynote. So we're going to have Mr. Stolyps

4:40ki, the CEO, he's going to go first and then

4:42hopefully

4:44jumping straight into some product updates

4:47and sort of directional things. I'm

4:49expecting a story.

4:50There's always a story these things, right?

4:53A story about data and a cautionary tale or

4:56something like that. Yeah, so we're good.

4:59We're even in HD. This is good. Okay. I was

5:02not banking

5:02on that. This is very nice. Cool.

5:04Apparently I'm a bit louder than you. I

5:06think that's just me.

5:08I can turn you down. Here's another benefit

5:12of being on a stream when you call, right?

5:15You can

5:15actually tap me down. I can turn myself up

5:18now. I'm now a lot. Also, I'm not talking

5:21to the mic

5:21directly, which is probably what it is. My

5:24mic is a bit more directional than your

5:26headset. So yeah,

5:27yeah, it's all good. It's all good. I've

5:29got the audio in the background as well. So

5:31that's good.

5:31Cool. Good. Right. So I've got a little bit

5:34of house cleaning up to do here. This is

5:37not quite

5:38how I wanted it. So I'm going to switch

5:40through the different feeds we've got at

5:41the moment.

5:42This is me. This is nice. And then this is

5:45Ravi. This is myself. Cool. And I think,

5:49I think this will have to do for the little

5:51thing, but I could probably do better. So

5:53let's,

5:54let's make this obvious just in case you

5:57don't know who Ravi and I are.

5:59Yeah, can't assume these things you see. Of

6:03course, it's 2020.

6:05Our identity is different. Our identity is

6:08different. Cool. So we've got what,

6:11three days of conference. And obviously

6:13this keynote is gonna be running tomorrow

6:14morning.

6:15I wonder if anyone's gonna watch this back

6:16tomorrow morning just to get the full

6:18experience.

6:18I doubt it. I doubt it. You either watch it

6:21live or you don't watch it at all. The

6:23YouTube is the

6:24next next one you'll actually probably

6:25watch, right? So this is Yeah. Good. Hello.

6:29Hello,

6:29Ben. coping. Apparently, it's a swish setup

6:31between the three of us. So I just

6:33literally

6:33got off the call with Ben. He's a good

6:35friend of mine. And he said he wanted a

6:37shout out

6:38live on there. So hi, Ben, how you doing?

6:40Great to have you on board. I trust you're

6:42going to

6:42finish watching the rest of the stream for

6:43the next hour and a half or something.

6:45Oh, we'll I mean, we have to. Exactly,

6:49exactly. Right. Now let me let me actually

6:51finish editing

6:52this OBS template because I want to go some

6:55bit more filler. So yeah, what we got so

6:59the first day

7:00or so today slash tomorrow, I'm not going

7:01to watch any sessions, I'm going to

7:03literally watch the

7:04keynote today this evening for the US time

7:06and then probably switch out to some some

7:08content

7:09tomorrow. My conference is a little bit

7:12different this year. As a Zen, I have some

7:14doctor sessions

7:15to do. So I'll be doing my half my days on

7:19Wednesday. On Tuesday and Friday, I've got

7:23some

7:23doctor sessions, but the rest of it is

7:25mainly brain dates for me, for me, the

7:26content. The value

7:29of conference to me in real life would be

7:31from from the interactions with people and

7:33getting to

7:34know devs a bit. And while I while I'm

7:36quite active with speaking, reaching out to

7:38devs directly,

7:38the people side is a bit difficult. So what

7:41I've done is I've set up a bunch of group

7:43group brain dates. I think this works

7:45almost better this year. There seems to be

7:49a lot more

7:49people using the brain dates platform. I

7:52guess it's less of a way to like, get from

7:54one end of

7:54the center to the other to make your brain

7:57day in time or leave a session early. So it

7:59's I think

8:00it's going to work out quite nicely. What

8:03else? What am I looking forward to? I guess

8:06that's a

8:06good good thing to five minutes to go is

8:09think a bit about predictions. My

8:11predictions for this

8:13session is I have a feeling that there is

8:17going to be a lot of Einstein. That's that

8:20's my Sherlock

8:21levels of deduction from the Sugar Daddy

8:23Salesforce need to sell some licenses,

8:25right? Yeah, exactly.

8:27Exactly. I think a lot of those will come

8:29from the the actual sessions. If you look

8:33at the sessions

8:34themselves, yeah, you'll see a lot of

8:36Einstein. But moving forward from that, I

8:39think from in

8:40terms of product updates, I'm expecting a

8:42bit more love given to server and online.

8:44That's my

8:46that's my prediction. Yeah. And hopefully

8:49my wish I guess is that we finally see

8:53next gen dashboards and dashboards get a

8:55bit of love. Okay. Yeah, yeah, yeah,

8:58exactly. Yeah.

8:59Yeah. But yeah, for me, since moving into

9:02my new role, I think I appreciate a lot of

9:05the

9:06server administrative tools a bit more. You

9:08know, my kingdom for a view as element on

9:13server where

9:13I give someone permissions and I want to I

9:15want to impersonate them. Yeah, that's the

9:17dream. And

9:18there's a couple of things I'm looking

9:20forward to otherwise as well. How about you

9:21, Tim? Now you're

9:22all set up? Are you all good with your

9:23setup? Pretty much all set up. Yeah, I

9:24think I'll have

9:25to settle for this conference. I'm actually

9:27looking forward to quite a few brain dates.

9:30I just put a

9:30small brain day out there for high quality

9:33video tutorials, basically. And I've had a

9:36few people

9:36reach out which has been great. Absolutely.

9:38I'm looking forward to meeting new people.

9:40I've set up

9:41my discord this week. So I'm gonna I'm

9:42gonna post that at some point in the stream

9:44somewhere. So if

9:45you know what discord is, hop into our

9:47server. I literally literally just finished

9:49setting it up

9:50this afternoon at some point. So hop into

9:52that and find out more about that.

9:54Otherwise, yeah, no,

9:55really looking forward to just seeing how

9:57the virtual setup is done. I'm not really I

9:59don't

9:59really have high expectations as such. And

10:01I think the content is going to have its

10:03own little focus.

10:03So yeah, we'll be able to be able to sort

10:05of evaluate that probably in a week's time

10:07on our

10:08on our next season of podcasts. Right? That

10:09's probably yeah, right. We're gonna roll

10:12over.

10:13We're gonna pretend that we finished the

10:15last season. Yeah, whenever we have a break

10:17,

10:17we just call it the end of the season. So

10:18here's the first question, right? So,

10:23right, right. What would your advice be for

10:25a brain dates newbie?

10:26Generally, don't don't fanboy the fan girl,

10:30right? Like don't just have a brain date

10:33with

10:33someone because they're cool. And then have

10:34a brain date with someone that you can get

10:36have

10:36access to anyway, like someone you already

10:39know, how brain dates with people who are

10:42talking about

10:42topics that you're really interested in,

10:45because you can kind of get lost in that

10:47sort of euphoria

10:47of conference. And it's very easy just to,

10:49you know, book yourself up and actually

10:51realize that

10:52all the conversations are the same thing,

10:53right? It's the same same theme. And, you

10:55know, I've got

10:56people come to talk to me about

10:58documentation and videos. And some people

10:59are talking about

11:00how they do their own product videos, not

11:02Tableau. So Red Hat, for example, is a

11:05topic

11:06that's come up. So that's a really nice way

11:08of sort of cross-validating because you

11:10have to have

11:10something to offer the person who's doing

11:12brain date, right? It's not just a one-way

11:13stream of

11:14information. You've got to be able to

11:16bounce off each other. So think of it as

11:17two people coming

11:18together rather than one person sharing

11:20knowledge with another person. I think I

11:22think alongside

11:22that, you know, if you're doing a group

11:24brain date, the trickiest part is, well,

11:27for me, at

11:27least, is trying to like get everyone

11:30involved. Yeah. Because I'm, I can steam

11:33roll a bit, and I'm

11:35aware of that. So it's trying to bring

11:36other people in this conversation. But it's

11:38also

11:38being that facilitator. So if you're in a

11:40conversation with, I think it's maximum six

11:43people in a brain date. Yeah. And, you know

11:44, there's three people talking and then the

11:46other

11:46two are just sitting there. They might be

11:48fine sitting there and absorbing and

11:50listening. But

11:51it's always good to like lean them up. And

11:53I think, again, if this is a real life

11:55conference,

11:55you talk about the horseshoe thing. This is

11:57something that Mark mentioned to me once,

11:59which is if you're sitting in something in

12:01the circle of people, you've got the hors

12:03eshoe,

12:03which is you don't close the circle, you

12:05have it open so someone else can step in.

12:07Yeah. Similarly, it's trying to create a

12:09virtual environment of that. I'm just like,

12:11I've just glanced across the screen and I'm

12:13so glad we're talking about something

12:15during this

12:15part. They're doing like a musical parody

12:19of. I didn't want to put them in full

12:22screen. So I've

12:22just literally created a little side thing

12:24on your screen. Hey, some people will get a

12:27kick out of it,

12:28so it's fine. But it's one of these things.

12:31If this was real life at the conference,

12:34you'd be sitting there like, oh, God, yeah,

12:36yeah, American. It's crazy. It's crazy. G

12:41osh. But now

12:42I'm actually looking forward to this. It's

12:45also Adam's first keynote as a subordinate

12:47in many

12:47ways. So what do you think? How it is?

12:51Absolutely. What's the word? Do you include

12:57last year's

12:58power struggle or dolphin impressions? I'm

13:01not going to try and recreate that here,

13:04but

13:05it was hilarious. Just just lost complete

13:08control. It was great fun. It's great fun.

13:11But I think so during the new year, this is

13:13this is going to sound really sad, but

13:15between Christmas and New Year, I spent a

13:16bit of time while I was in the intervention

13:18,

13:18I'm looking at Benioff. Yes. I was trying

13:20to understand the sort of ethos beyond

13:22Salesforce and

13:23trying to get a grasp on what's going to

13:26happen. And my takeaway, he does he does

13:28random stuff

13:29like that a lot. That's okay. That's just

13:31him. And I think there's a lot of times he

13:33sort of derails

13:34the conversation at the start and then

13:36brings it back in, which I think what he

13:37did, I think

13:37the problem with the tableau where I was

13:40sat at the front. So everyone else was the

13:43disrespect.

13:44Right. But if you then if you ignore that

13:45first section, then listen to what he says.

13:47He's really

13:48smart and on board and he's dug into

13:50everything that that tableau do. And I

13:53think the Salesforce

13:54ethos is somewhat similar. Yeah. Right.

13:57Like, yeah, that's true that they do have

13:59deep roots

14:00and groundings and real people are trying

14:02to solve actual problems. Yeah. And I think

14:05the key

14:05difference is it's not cult. There's not a

14:07cult like following like tableau has.

14:09Absolutely. So

14:11we've got a couple more people dropping

14:13comments. Anna, any any advice for you? You

14:16've done that

14:17one. Volantis, holla, how you doing? Hey,

14:19Volantis, all the way from Buenos Aires.

14:21Yeah, I was about

14:22to say like, where are you? Where are you

14:23right now? I never know where he is. Yeah,

14:25everyone,

14:25everyone drop a comment like just shout out

14:27where you are. I'm in Chelmsford, Essex.

14:29It's courage. Essex. We should just call

14:32this the Essex live stream. Like,

14:34the only way is Essex. Hey, here we go.

14:38There we go. There we go. It's hilarious.

14:42Excellent.

14:43Excellent. No, so we're gonna do the same

14:45thing again, as we have done today. I think

14:46we'll have

14:47a shorter pre show. But the section will be

14:50always starting. We're starting very

14:53shortly now. Right,

14:55right. We're gonna do Devs at desk as well.

14:56Right. So let's let's take a pause and just

14:58listen.

14:58For understanding, for insights, for

15:05answers. This is the time for data people

15:09to come together.

15:11The power of data and make this is the

15:13moment of conference. I'm just like,

15:15I might be crumple the time but this is fun

15:17. Welcome to here we go. Here we go.

15:21I was wondering if they bring back a list

15:24of things to do the voiceovers on up.

15:27Oh, this is cool. It's very Apple. They're

15:30doing it. They're doing it.

15:40Excellent. There he is. There he is. He's

15:44been green screened in.

15:45Aren't we all? Right. Let's start.

15:50Slipski CEO of Tableau. Welcome to Tableau

15:54conference ish. Thank you so much for

15:57joining

15:58us in this new venue. I have to admit this

16:00is new. I've been adjusting to sitting at

16:03home,

16:04presenting to folks with a cat on my lap,

16:06hearing the neighbors dogs barking and

16:08seeing one of my

16:09kids doing yoga down the hallway. I know we

16:11've each had our own reality the past six

16:14months,

16:14and that it's been hard for so many. While

16:17I truly wish we could be together in person

16:20,

16:20TC is the highlight of the year for us at

16:23Tableau. I'm so happy to be able to be with

16:25you ish now.

16:27How many times is he going to say ish do

16:29you reckon?

16:29It's so bad for SEO.

16:33Ish.

16:36Ish.

16:36Hey Trailblazer. I've missed the Trailbl

16:55azer reference. Very good.

16:57Get rid of Zenmuss' big on more Trailblaz

17:02ers.

17:02Even virtually with our data fam is so

17:05inspiring. And let's be honest,

17:08after the year we've had so far. How long

17:09till we get the first match of ubiquity?

17:11And some inspiration. It's been a tough

17:14year. We're worried about the health of our

17:18families,

17:18friends, communities, and the world. We're

17:21worried about our jobs and the economy.

17:24Some of us are desperate for a few moments

17:26of quiet in our busy homes.

17:28I think he's reading from an autocue.

17:33Yeah.

17:33But then again, so did Apple, right? If you

17:38see them just...

17:39I think on a couple of them you can see the

17:41thing on their glasses.

17:42Right. But I think his is slightly camera.

17:45His head is angled that way.

17:48Kind of critique a producer would do.

17:51No one cares.

17:55We're in a war on data to help us make

17:56sense of a world that feels so out of

17:58control.

17:59This year, every big story was a data story

18:03.

18:04Data made the term "flatten the curve,"

18:06part of our everyday language.

18:08Data is how we understood the spread, the

18:11global trends, and the human cost of COVID.

18:14Data is how we understood the heart-st

18:16opping economic impact of this pandemic.

18:20And data shows promise as a powerful tool

18:22to aid the fight for racial equality and

18:25justice.

18:25We've always said that we all are data...

18:28That's a great vis, actually. The exoner

18:30ations one. Really, really good looking.

18:32But the role that data played in these

18:34crises goes far beyond simply driving

18:36understanding.

18:37Data drove critical decisions. Data created

18:40impact.

18:41Clearly uses syntax for the vis public

18:43gallery.

18:44Think back to February of this year.

18:45Yeah, I think so.

18:46Honestly, I know it feels like a...

18:47Well, it's nice. It's the same. It's a

18:49consistent look and feel.

18:50Right. They had a budget. They had to

18:52stretch it.

18:53Before flaring around our shores in America

18:55.

18:55But it's a crisp green screen, right?

18:57Yeah, it is. It is.

18:58You'd expect nothing less from that kind of

19:01scale of companies.

19:02Probably the sales forces compared to what

19:04cities like New York experienced.

19:06Well, this is... It's like...

19:09So I'm really looking forward to next year

19:11and actually always looking forward to this

19:12year.

19:13Just the budget. Like, imagine a budget.

19:15Like Dreamforce had Obama and Fleetwood

19:17back.

19:18Like, imagine what we're gonna have next

19:19year.

19:20Yeah. When did they just say Dreamforce

19:22Tableau? One conference.

19:23And when it's financially viable, not a Tab

19:28oo.

19:28Absolutely.

19:31Shouts to key workers.

19:34Yeah. Very good.

19:36Very good.

19:36City agencies stepped up with a secret

19:39weapon to help in the fight against COVID-

19:4219.

19:42Data.

19:43To marshal the right resources, to flatten

19:45the curve and save lives.

19:47That secret weapon was data.

19:50How did I guess?

19:51Nailed it.

19:52We've asked Kelly Jin, the Chief Analytics

19:55Officer of New York City, to join us.

19:57Kelly was at the eye of the storm, helping

20:00to oversee the administration's use of data

20:03to respond quickly to the crisis.

20:05Kelly, first of all, thank you for joining

20:08me.

20:08Wow. I mean, it felt like the entire world

20:10's eyes were on New York this spring.

20:13It really did. It really did.

20:14And it's a pleasure to be here with you,

20:16Adam, and everyone for the conference.

20:19Excellent. Well, it's so exciting to have

20:21you here.

20:22What did it feel like when you and your

20:24teams were in the midst of this crisis?

20:26It really was literally the eye of the

20:30storm for us.

20:32So we were at the Emergency Operations

20:34Center, which is right down the street from

20:37me here

20:37in Brooklyn, 24/7.

20:39The other interesting thing is when you're

20:43looking at people's backgrounds now in

20:44their

20:45offices, it's just like, is that your

20:46actual office or is it a Zoom background?

20:50Yeah, exactly.

20:50Because they're so good.

20:52I think they've all had the same sort of

20:57stream consulting kind of talk to them and

21:00get

21:00everything sorted.

21:02Just setting up a tweet.

21:04That's why I'm distracted.

21:06That's right.

21:06Vansy has just mentioned, Tableau probably

21:09got a huge spike on traffic the first few

21:10days.

21:11Yeah, absolutely.

21:11I think they actually had to upgrade the

21:14servers because it was a ridiculous spike.

21:17So they did loads of backend development at

21:19the start of COVID.

21:22It's no surprise that if you invest a bit

21:23in marketing and putting that stuff out

21:26there

21:27in a good place, it works really well.

21:28So people like that.

21:34Tim, maybe turn us a little bit down.

21:36I think they can't hear us when we chat or

21:38they can't present when we chat.

21:39I don't know if we can balance that out.

21:41And so for us, we have a long tradition of

21:44working within emergency here in the city

21:47within my office.

21:48And it was very, very critical that we not

21:50only delivered, but that we partnered with

21:53many different city agencies, including the

21:55fire department, the emergency management

21:58department here, as well as Department of

22:00Health, but many, many others.

22:02And I think one of the most interesting use

22:05cases and stories that we saw in the spring

22:08time

22:08for us here in New York City was around how

22:13do we assess the availability of ICU beds.

22:16Of course, you can imagine that's a data

22:18integration effort across many, many

22:20different

22:21sources and then actually use that data to

22:24derive where should we be sending ambul

22:27ances

22:28to.

22:29And I was very, very thrilled to have Table

22:32au support and help.

22:34I used to work for US Chief Data Scientist

22:36at the White House, DJ Patil, and he oft

22:39entimes

22:39used this term of force accelerators.

22:42And I know the Tableau team, you certainly

22:44all were force accelerators in springtime

22:47for us.

22:47You came in, helped really to build out

22:49those data visualizations, whether that's

22:52regarding

22:53ICU beds or many, many other operational

22:55use cases to help us actually make better

22:58and

22:59faster decisions here in New York City.

23:00>> It's just amazing using data to tell

23:05ambulances where ICU beds are available.

23:08Incredible.

23:09So what did you and your teams learn about

23:11being ready for future crises?

23:13>> Well, it's all about understanding what

23:17data you have.

23:18So for us during Blue Skies, and I

23:21recommend this for every organization out

23:24there, it

23:25is critical you understand all of your data

23:28assets first and foremost.

23:30I know data cataloging may not be at the

23:32top of everyone's minds, but it was

23:34critically

23:35important to us through the COVID response

23:37to know what was out there, what was

23:39available,

23:40and what could we actually lean on to help

23:42make decisions using data.

23:45And I think the second is I'll say that I

23:48really recommend that folks continue to

23:51invest

23:51in their analytics teams, in their data

23:54scientists.

23:55We are a small office of ten here within a

23:58very, very large ocean of New York City.

24:01And I know for many jurisdictions, those

24:03that had robust data teams, analytics teams

24:07really

24:07were the ones that were able to get their

24:09arms around the response.

24:10And I think we'll be that much more

24:13understanding around what the current and

24:15the future states

24:16will be around recovery as well.

24:17>> You've made it through so much, and now

24:21the city is also focused on recovery.

24:24What role is data playing in that effort?

24:26>> Data will still be integral around

24:29recovery.

24:30And I think for all of us keeping up with

24:33the news and current events, that will

24:35continue

24:36to be true.

24:36I think what was really pivotal for us

24:39early on, even through response, was

24:41understanding

24:42how different industries were doing.

24:44And so, Adam, you can imagine here in New

24:46York City wanting to understand how many

24:49restaurants

24:49are there in total, how are they all

24:51changing their hours, and what is the

24:54impact to COVID

24:55more broadly.

24:56And that extends into the housing and real

24:58estate markets and many, many other sectors

25:01as well.

25:02At the end of July, we were very fortunate.

25:05We launched the New York City recovery data

25:07partnership, which is an initial cohort of

25:1011 different data partners.

25:12Some of the larger ones include Foursquare,

25:15LinkedIn, as well as StreetEasy.

25:17>> I always wonder how much does this

25:19change your data flow.

25:20>> And for us, this is all about data

25:22sharing.

25:23So, what data can we work with private

25:25sector companies on so that we're actually

25:27receiving

25:28more high-frequency, real-time data to

25:31inform our policy and decision-making.

25:33And I'm very, very excited to see how this

25:36partnership continues to grow in the

25:38upcoming

25:39months and in the year ahead.

25:40>> Honestly, what an amazing story.

25:43Thank you so much, Kelly.

25:45I know that I speak for all of us when I

25:47say how much we admire you and your teams

25:49for

25:50the work you did and what you're continuing

25:52to do.

25:52And we all look forward to seeing New York

25:54come back stronger than ever.

25:55>> Thanks so much, Adam.

25:57It's a pleasure to be here with you and a

26:00privilege and look forward to hearing more

26:03about the conference.

26:04>> Well, be well and thank you again.

26:05The New York City story was obviously

26:08dramatic.

26:09But the issues they faced were far from

26:11unique.

26:12>> All done in post.

26:13>> I know from conversations I was having

26:15with customers, governments, companies, and

26:17people all over the world were struggling

26:19to figure out how to respond.

26:21They were flying blind without access to

26:24clean, accessible data that they needed to

26:26make critical

26:27decisions.

26:27Tableau, with the help of our amazing DataF

26:31am, created the COVID-19 Data Hub to answer

26:34that

26:34need.

26:35We worked with partners to find multiple

26:37public data sources, combine them, clean

26:40them, and

26:40make them all available.

26:41Anyone could now analyze this data and even

26:45add in their own critical data.

26:47>> I think it is worth mentioning the data

26:47ethics.

26:47>> We also built a global COVID tracker

26:50with the latest analysis of COVID cases and

26:52hot

26:52spots for every country in the world.

26:54>> Post about the silence after the spike.

26:55>> Our amazing community has created over

26:5730,000 visits on every aspect of this

27:00crisis.

27:01Our partners created Jumpstart workbooks in

27:04critical areas such as human resource

27:06analysis.

27:07And the hub includes guidance on

27:09responsible and ethical use of sensitive

27:12data during this

27:13crisis.

27:13These resources have been viewed millions

27:16of times.

27:17And tens of thousands of organizations are

27:20relying on the hub.

27:21Lockheed Martin relied on Tableau to

27:23support operations during the COVID pand

27:25emic.

27:27A massive West Coast healthcare system was

27:29able to redistribute supplies and medical

27:31staff

27:32to hot spots.

27:32Humanitarian organizations like UNICEF,

27:36consulting firms like Deloitte, healthcare

27:38providers

27:38like UNC Health, and researchers like MIT

27:41have all relied on the COVID Data Hub to

27:44inform

27:44the public and to drive many of their most

27:47important decisions.

27:48It even got Hollywood's attention.

27:51Ashton Kutcher tweeted about it.

27:53I'm so proud of this community.

27:57You've helped so many people when the world

28:00has needed you the most.

28:02Now in most years, COVID wouldn't just be a

28:06huge story.

28:07It would be the story.

28:08>> What's the weirdest shout out you've

28:09ever got?

28:09>> COVID was just the first crisis to

28:11dominate the news this year.

28:12As more information about COVID cases in

28:15the US came out, it started to foreshadow

28:17another

28:18major crisis.

28:19Visits like this one made it crystal clear

28:21that COVID is disproportionately impacting

28:24the black community and other communities

28:26of color.

28:27But look at criminal justice, healthcare,

28:29housing, education, unemployment, name a

28:32social

28:32issue and it's likely impacting communities

28:35of color disproportionately.

28:36More broadly, the systemic inequality and

28:39racism that still exists in so many arenas

28:42is something we must address.

28:45And I firmly believe that this is one area

28:48in which Tableau can and should contribute

28:51uniquely, data.

28:54Data can influence change at every level

28:56from local government to federal agencies,

28:58businesses,

28:59community organizations.

29:00However, so many people working to drive

29:04racial equity are frustrated by the disag

29:07gregated,

29:07incomplete, inconsistent data that they

29:10must wrangle.

29:11There simply is no central repository for

29:15that data.

29:15And that's a significant hurdle.

29:19We've heard repeatedly that one of the most

29:21powerful ways that Tableau could help in

29:23this

29:23march for change would be to put our

29:25shoulder to the wheel alongside wonderful

29:28organizations

29:29already working on this difficult data

29:30problem.

29:30Your volume is coming through my headset.

29:32Organizations like PolicyLink, a national

29:34research and action institute dedicated to

29:37advancing economic and social equity.

29:39I'm so proud that Tableau is working with

29:43PolicyLink, the Urban Institute, and other

29:46leading organizations, and together we

29:48formed a racial justice data initiative.

29:51Together, we're making grants of software,

29:54services, and direct funding to support

29:56advocates

29:57and community organizations who will drive

29:59action at every level from local to

30:01national.

30:02We're also standing up a rich data hub to

30:04connect people with data and resources that

30:07they need to do this work.

30:09Tableau is committing $12 million to this

30:12effort.

30:12To hear more about this partnership to

30:15bring data to racial justice, it's my honor

30:18to

30:18talk with Dr. Michael McAfee, the CEO of

30:21PolicyLink.

30:22Michael, thank you so much for joining me

30:24here today.

30:25>> Thank you for having me.

30:27It's an honor to be here.

30:28>> I'm really excited for our audience to

30:31hear from you directly.

30:31So why don't you take it away?

30:33>> I'm honored to be here today because in

30:36some ways this is a new audience for me,

30:39but

30:39it's an important audience.

30:41Whether you know it or not, you are at the

30:43edge of the equity movement.

30:45And you're at the edge of the equity

30:47movement because your brilliance and your

30:49insights

30:50and your data tools are doing something

30:53that we've long needed in the racial equity

30:56, racial

30:56justice movement.

30:57You're lifting the veil of ignorance.

30:59You're lifting the veil of ignorance around

31:01structural oppression that has been in

31:03place

31:04for more than 400 years in this country and

31:07how it impacts folks, people of color,

31:09white

31:10folks who get swept up in it.

31:13And you're also helping to bring voice to

31:15people who have for many years been saying

31:18their communities are not sustainable.

31:21Their communities are suffering and no one

31:23has listened.

31:24And so I'm excited to join you today

31:26because I've seen firsthand the power of

31:28data, the

31:29power of data analysis, and the power of

31:31having conscious leaders who know how to

31:34put data

31:34in context and to lead on that data.

31:37So I want to share a couple of observations

31:40and an invitation.

31:42For you to think about them.

31:43The first observation is this.

31:46That in this moment of racial awakening,

31:51data is critical to our understanding of

31:54how to

31:55move forward and how to craft solutions

31:57that actually really work.

31:59You have the capability right now to help

32:03join with the racial justice movement to

32:07ensure

32:07that that energy from the street gets

32:10translated into public policy.

32:13That designs a world where everyone can

32:14participate, prosper, and reach their full

32:17potential.

32:18Now that's no easy task.

32:19That task only happens if we can use data

32:23in a couple of ways.

32:25The first is if we can begin to disaggreg

32:27ate it so that we can actually see the

32:29humanity

32:30of folks in those data sets.

32:31So that we can see their unique stories,

32:33their unique challenges, the unique ways in

32:36which

32:36they experience structural barriers to

32:38opportunity in this nation.

32:41We are at the early stages of being able to

32:43disaggregate data and have the right data

32:46sets that we need.

32:46That's why this partnership with you all in

32:49Tableau is so important.

32:51You're going to be giving us those tools to

32:53actually strengthen our data capacity.

32:56And so disaggregating data is essential if

32:59we're going to have really good equity

33:00conversations.

33:01But the second is to be able to put that

33:03data in context.

33:04Now I'll give you a really good example.

33:06- This is what you talk about a lot.

33:08Like you can't, if you don't have a bench

33:09plan.

33:10- We've been participating in conversations

33:12around COVID data since this pandemic

33:14started.

33:15And we haven't been able to have good

33:17context for that data.

33:19In some meetings that I've been in, some of

33:21the medical professionals were concerned

33:24about

33:24even putting disaggregated data out there

33:28because they were concerned that it would

33:30cause people to not want to invest once

33:32they saw that the folks who were being most

33:34impacted

33:35are disproportionately impacted were poor

33:37folks, low-income folks, people of color.

33:40And so there have been there's host of

33:42conversations.

33:44Now while there is no causal data that says

33:46that disaggregating the data and putting it

33:49out there causes people to not invest, the

33:52history of structural racism in this

33:55country

33:56has people fearful of that reality.

33:59And so this is why having good quality data

34:02to guide strategy, to guide policy

34:05decisions

34:06is so important.

34:07You've been giving us insights into who's

34:10been hurt first and worst by this pandemic.

34:13But even more important, what you're about

34:15to help us do with this racial equity hub

34:17is to take our National Equity Atlas work,

34:20which is the preeminent racial and economic

34:22scorecard for the nation.

34:23Take that work to the next level.

34:27The work for our generation is to use

34:29everything at our disposal—the rigor of

34:33the data science,

34:34the rigor of data tools—to bring about a

34:37just and fair society in which everyone can

34:40participate, prosper, and reach their full

34:41potential.

34:42Some people think that's wishful thinking.

34:44Some people think that that's a soft idea.

34:48It is not.

34:48If this nation is going to get beyond

34:51having 100 million folks in this country,

34:54one in

34:54three people who live in this country who

34:57are economically insecure, get out of that

35:00predicament, it's going to take all that we

35:02have.

35:02This is such a—it's putting it in front

35:05of the centimeter.

35:06This is what Tableau is about.

35:07That allows us to craft solutions that

35:09allow us to create an equitable nation, a

35:13nation

35:13where you have healthy communities of

35:15opportunities, a just society, and an

35:17equitable economy.

35:18Thank you.

35:19Michael, it's an honor to be working

35:21together with you and our other partners.

35:24Thanks so much for joining us here.

35:25Boom indeed.

35:28Take care and look forward to talking to

35:29you again soon.

35:30All right.

35:31Bye-bye.

35:32Michael just mentioned the National Equity

35:35Atlas.

35:36It's such a rich source of data, and I

35:38encourage you to check that out.

35:39Our equity data hub, launching soon, will

35:43have tools and resources to empower you to

35:46make changes in your own communities.

35:49It will also include opportunities for our

35:51Tableau community to learn, create, share,

35:54and explore visualizations.

35:56To sign up for an alert when the hub goes

35:59live, go to TableauFoundation.org.

36:02Now, there's another real crisis in 2020

36:07that we haven't talked about yet, the

36:09economic

36:10impact of COVID-19.

36:12Many industries and much of the entire

36:14economy froze overnight.

36:17Here in the U.S., 14 million people became

36:20unemployed in three months between March

36:22and

36:22May.

36:23The World Bank forecasts that the global

36:25economy will shrink by more than 5% this

36:28year, the

36:29deepest recession since the 1930s.

36:31We all scrambled to find our footing in

36:33this new reality.

36:35Thinking back to those early days, the

36:38pressure to make the right decisions was

36:40immense.

36:41Do we stop traveling?

36:43Do we keep our offices open?

36:45How do we keep employees safe?

36:46How do we keep our businesses healthy?

36:48I grappled with these same questions.

36:51These were massive decisions that would

36:54impact not just our thousands of employees,

36:56but their

36:57families and our customers and other local

36:59businesses.

37:00Completely, yeah.

37:01It's just one of these things that no plan

37:03could ever prepare you for.

37:05I also rely on my body of experience, my

37:08intuition, pattern matching from what I've

37:10seen before,

37:11whatever you want to call it.

37:12Often that's a good thing.

37:14[LAUGHTER]

37:14Is it YouTube's caption or Tableau's?

37:16And absolutely none of my experience

37:18applied.

37:18That's even worse.

37:19It's Tableau's.

37:20Instinct and experience weren't just as

37:22useless.

37:22Because you either had time to like, ah,

37:23anyway.

37:24Actively unhelpful.

37:25It was not like anything else.

37:28It's live, right?

37:28It's live.

37:29[LAUGHTER]

37:29And with all the assumptions you have about

37:32how the world works turned upside down.

37:35When the laws of physics no longer seem to

37:37apply, your normal ways of thinking can

37:40lead

37:41you down a very bad road.

37:43My instincts told me to remain steady, not

37:46to be so reactive.

37:47Canceling in-person meetings, that's a bit

37:50paranoid, right?

37:51Closing our offices, whoa, you'll cause a

37:54panic.

37:55And what if you're the only company to do

37:57it?

37:57When instinct failed me, I turned to my own

38:01secret weapon.

38:03I had data.

38:04And data helped me push back against my own

38:07instincts.

38:08It helped me understand the reality that we

38:10were in.

38:12Data helped us run our business in wildly

38:14unfamiliar circumstances.

38:16So I hate the term secret weapon.

38:18There's an article about Liverpool's secret

38:20weapon.

38:20And then they just go into it.

38:21It's like, well, it's not secret then, is

38:22it?

38:23Like, stop saying secret weapon and saying

38:25what your secret weapon is.

38:26[LAUGHTER]

38:27Exactly.

38:28This is how we monitored employee health.

38:30And it wasn't a secret weapon.

38:30This is how we adjusted our sales

38:32approaches to make sure we were relevant

38:34and helpful to customers.

38:35It's like Pikachu meme face.

38:36This is how we understood the impact of

38:38finance and to marketing.

38:40In the most volatile business environment I

38:42have ever experienced,

38:44the one thing I could rely on was data.

38:46I wasn't alone.

38:48Across the globe, we've talked to

38:51organizations who leaned on data to make

38:53critical decisions,

38:54to stay relevant to customers, and to save

38:57jobs

38:58while facing challenges that none of us had

39:00ever faced before.

39:01Like Mod Pizza, they're relying on Tableau

39:05for rapid contact tracing to safeguard

39:07customer first--

39:08Again, the second thing I'm really glad

39:10about--

39:10--is everyone slamming dashboards that come

39:13on.

39:14COVID prevented them from traveling--

39:15This is real.

39:16This is what most people do.

39:17Like, don't be like, this needs to make a

39:19Monday, which I'm sure no doubt is

39:21happening

39:21over on Twitter.

39:23--were loaded on container ship.

39:24Literally, if it answers a question, it

39:26doesn't matter.

39:27--their quality control--

39:28Right, exactly.

39:28--how would they even operate?

39:29It's like being a scrape.

39:30--and Henkel, the massive European chemical

39:33and consumer goods company--

39:34And ultimately, if it's giving the people

39:37the answer they need--

39:38--the right PPE for their employees--

39:39--in the back.

39:40--in each location.

39:41Hard truth, mate.

39:41Hard truth.

39:42Without this, they cannot keep their

39:44factories running.

39:45Data has asserted its place as a critical

39:49enabler during these crises.

39:51But it's important to remember that it's

39:54not just about crises.

39:56Data is only going to become more important

39:58in the days and years to come.

40:00Just look at what's happened with the pace

40:02of digital transformation.

40:05A year ago, the world was already on a

40:07strong pace, marching relentlessly

40:10towards analytics ubiquity.

40:11Yay!

40:12But by March of 2020--

40:13Yay!

40:14--it was like we were strapped to a digital

40:16rocket ship.

40:17[LAUGHTER]

40:18McKinsey & Company estimates we experienced

40:20five years worth of digital adoption in

40:23eight weeks.

40:24And every digital transformation is a data

40:27transformation.

40:29Everything digital creates data.

40:31And we need to use all of that information

40:34to adjust to new scenarios,

40:35to deliver the best possible customer

40:37experiences, to keep businesses going.

40:402020 has proven everything you'd ever want

40:44to know about the role of data.

40:46Insight from data is saving jobs.

40:49Insight from data is saving lives.

40:51The superpower that data enables, the one

40:56that's driving these results, is adapt

40:58ability.

40:59The ability to understand true facts, not

41:02what you once knew and not what you wish

41:04were true.

41:05True facts.

41:06And to pivot nimbly in response.

41:07[LAUGHTER]

41:08Adaptability has become a critical

41:10competence.

41:11So in order to adapt at the pace you need,

41:15what does your relationship with data need

41:17to look like?

41:17Are we about to get some blueprint, love,

41:18or not?

41:19What do you reckon?

41:20First, you need to understand things fast.

41:23Oh, yeah.

41:24When New York City was facing exponential

41:26growth in COVID cases,

41:27accelerating decisions was literally a

41:29matter of life and death.

41:31Second, you need the full picture so you

41:35can identify--

41:35You're never going to guess that one.

41:37[LAUGHTER]

41:38Michael from PolicyLink already showed us--

41:40Agility will come into this.

41:41--what a barrier it is not having the full

41:43picture on racial justice data.

41:44Third, you need to empower everyone across

41:48the organization to use data to drive

41:50better decisions.

41:51Pfizer, JPMorgan Chase, Woolworths, Honey

41:55well, Nissan,

41:56all have deployed Tableau to tens of

41:58thousands of employees.

41:59In any industry you can name, empower your

42:02--

42:02Power your individuals for analytics.

42:04--by empowering everyone from the factory

42:07floor to the dealerships,

42:08from customer service to the executive team

42:10, to drive impact from top to bottom.

42:12Since our launch nearly 17 years ago, Table

42:17au has been singularly focused on helping

42:20people see

42:21and understand data.

42:24Over that time, we've been building the

42:26broadest and the deepest analytics

42:28capabilities in the

42:29world. We have the most expansive and

42:31enthusiastic customer base, and you are

42:34growing data cultures

42:35within your organizations.

42:37Here we go.

42:38We've been relentlessly focused on your

42:40success.

42:41And then a year ago, we joined together

42:44with Salesforce.

42:45It's proven to be an incredible team up.

42:48We share a belief that data is changing the

42:51world.

42:52We share a commitment to making data the

42:55heart of digital transformation.

42:57Are you going to get Benny off or not?

42:58Joe Atkinson, the Chief Products and

43:00Technology Officer of PwC,

43:02global service services company, has

43:05firsthand experience with leveraging the

43:07power of our

43:07combined data and analytics capabilities to

43:09serve clients and their employees.

43:11I disagree.

43:12If it was a real one, I don't think you

43:13would just to show Tableau's its own thing.

43:16To share his experience and how data is

43:18shaping their digital transformation and

43:21the way that

43:21his team works with Salesforce and Tableau

43:24on a daily basis.

43:25Joe, it's so great to have you with us.

43:27Thanks for having me, Adam.

43:29Excited to be here.

43:30I was delighted you were able to join us

43:33because PwC has had so much success with

43:35integrating

43:36analytics and data in the daily processes

43:39using both Salesforce and Tableau.

43:41If it was live.

43:41How have you made data analytics a part of

43:43your PwC?

43:43I think they really do want to say it's

43:45still its own company for now.

43:46We were fortunate enough a few years ago to

43:48see the writing on wall.

43:49At least I think it's been five years

43:50before they start being rolled in.

43:52But there's a few ways out.

43:54So we made a massive investment for our

43:58firm.

43:59Three billion dollars over the course of

44:01the last few years to help skill them and

44:03provide

44:04them the tools that were going to help them

44:05serve our clients and our communities and

44:07frankly each other better as colleagues and

44:09employees.

44:10And that's been huge because we looked at

44:12everybody.

44:13We didn't take it by role or title or

44:15tenure.

44:16You spent three billion on scaling your

44:18entire global organization.

44:20And at the same time bring those tools to

44:22our clients.

44:23How much of a success rate do you need to

44:25say that was a success?

44:26Where we could lower cost.

44:27So Joe, how are you and your teams looking

44:31to use data analytics to adapt to a rapidly

44:34changing environment like the one we're all

44:35in today?

44:36Then suddenly using data day to day.

44:38You know Adam, I say often that I don't

44:40think any of us could have predicted the

44:42kind of

44:43challenges we're all facing today.

44:45It's self-fulfilling prophecy.

44:46In today's environment you've got

44:47volatility, you've got uncertainty, you've

44:50got commitments

44:51we're all making to our clients and our

44:52employees about how we're going to navigate

44:54through

44:54all this.

44:55That requires a lot of good insights to be

44:57at the ready and it needs to be seen and

45:00quality

45:00and all of the attributes we look for need

45:02to be there.

45:03So when you have that, to have the kind of

45:05technology tools available to us, really

45:08critical.

45:08But if you have those technology tools

45:10without people that know how to use them

45:11and put them

45:12to work, then it's not going to get you

45:14very far.

45:14And so our ability to take advantage of the

45:16investments that we've made in upskilling

45:19and training our people and giving them

45:21those data skills and then bringing the

45:22technology

45:23to bear with them, that's been critical to

45:25us navigating through this really

45:27challenging

45:28period.

45:28So here's a what if for you.

45:30Multifastic.

45:31If you hadn't gone all in on data culture

45:33several years back, how different would

45:36your

45:36situation be today after the series of

45:38challenges that you faced this year?

45:40I'd love to know how much that trillion was

45:41spent by PwC itself.

45:42There's no question in my mind, Adam, we'd

45:44be behind and in fact, we may be way behind

45:46.

45:46Does that make sense?

45:47So internal spend versus external spend.

45:50Yes, they're coming to the realization now,

45:52unfortunately, that they need to start

45:53making

45:53these investments and they're really

45:55playing catch up to try to get the skills

45:57they need.

45:57And here's a good question.

45:58How do you measure the success?

45:59And this is it, right?

46:00Because that's not just the current

46:01environment.

46:01It's the way the business operates today.

46:03Reducing time to insight, return on

46:05investment.

46:06There's a few ways, but you have to define

46:07that really early.

46:09Otherwise, it's just 3 million into the fan

46:11.

46:12Well, measuring it helps us make the pivot

46:15in the pandemic.

46:16It helps us create value during very

46:18challenging times and our clients have

46:20noticed.

46:20We're getting McKinley in.

46:23Yeah, exactly.

46:23PwC gives out a lot of advice.

46:25You've given us a lot of great advice over

46:27the years for companies looking to invest

46:30in their own digital transformations with

46:32data at the core.

46:33What would your advice to them be?

46:35You know, Adam, a lot of companies are

46:37under a lot of security and I recognize

46:39everybody

46:39doesn't have the same investment capacity

46:41that they may have had previously.

46:42We've slowly taken that.

46:43It could not be more important to keep

46:45investing in digital skills and technology

46:48today than

46:49it's ever been.

46:50And I think understanding that these

46:52investments are critical today, not again,

46:54just not for

46:55navigating through the pandemic, but where

46:57this all takes us and what business looks

46:58like.

46:59I think that's the first critical piece.

47:01Don't let up on the accelerator if you have

47:03the ability to do that.

47:04The second piece I would say is if you

47:07think about jobs, I often say there's

47:09a whole conversation we used to have as

47:12leaders and employers of tech jobs and non-

47:14tech jobs.

47:15The reality is there are just jobs and they

47:18all are going to require technology skills.

47:20People will have to be comfortable with

47:22applying the kind of tools and technologies

47:24that bring

47:24insight, that bring that rapid

47:26understanding of what's happening in the

47:28environment.

47:28So bringing that together is really

47:30important.

47:31And last but not least, there's a really

47:33important role for the right technology and

47:36tools and

47:36a tech transformation, as you know.

47:38But there's also a huge important element,

47:41which is getting the talent where you need

47:43the talent to go.

47:44And that's, I think, an obligation many of

47:46us share as employers.

47:47Obviously, the employees have an obligation

47:49in this transaction, people in this

47:51handshake.

47:52But I think as employers, we've got to help

47:54equip our people with the skills that not

47:56only make them more relevant in our

47:58employee today, but wherever their careers

48:00take them.

48:01We've got to build them up and help them

48:02get where they need to go.

48:03If we can do that the right way, everybody

48:05wins.

48:06But that's a good way of thinking about it.

48:09It's like, we don't care if you leave.

48:09We just want to steal you anyway, because

48:11it's helpful for the world.

48:12But yeah, I guess PwC is one of the few

48:14companies that have the luxury of saying

48:16that, even

48:16though they just have a churn of income

48:17from the graduates.

48:18They have a high churn, like what, 10%, 20%

48:21?

48:21So yeah, it's quite high.

48:30I'll turn my volume up to try and balance

48:33off my levels.

48:34Thanks for the time, and I hope you all

48:36have a great conference.

48:37Thanks again.

48:38Be well.

48:38Talk to you soon.

48:39Talking to customers like PwC is a great

48:45reinforcement of why we're so excited to be

48:47part

48:47of Salesforce.

48:48So 10 more minutes of Adam before it's

48:51roadmap time.

48:52Sophisticated AI and machine learning

48:54capabilities that Salesforce has built.

48:56More coming on that in a few minutes today.

49:01We can further embed analytics right into

49:03the flow of applications that people are

49:05using

49:05today.

49:05We can create a better platform and better

49:08experiences for you.

49:10I was optimistic a year ago, and everything

49:14I've seen since makes me absolutely sure

49:16that

49:16this was the right choice for us, and more

49:19importantly, for you.

49:20Earlier this year, we brought together--

49:23Ohana.

49:24--Tablo--

49:24That's the next--

49:25--Einstein Analytics team is under one

49:26group.

49:26Ohana is the next one.

49:27Two unbelievably talented teams--

49:28You can put that in the day together, Ohana

49:31.

49:31--now working together to make analytics

49:32even more powerful and delightful.

49:34We're also bringing together the best Table

49:37au capabilities and the best of Einstein

49:39Analytics.

49:40Over time, these capabilities will work

49:42more and more seamlessly--

49:43[INTERPOSING VOICES]

49:43--to unlock amazing new experiences.

49:46We're going to show you more about that

49:48today.

49:48Add in the power of the rest of the Sales

49:51force portfolio, and you have the world's

49:54leading

49:55analytics platform made broader and deeper

49:57than ever before.

49:59We're going to take a short break now, but

50:02don't go too far.

50:04When we come back, our Chief Products

50:05Officer, Francois Aschinsdatt--

50:07Cool.

50:07Break time.

50:08--is going to take you through our latest

50:09platform innovations and talk about how we

50:11're

50:12bringing this incredible vision together.

50:14We'll see you in about five minutes.

50:14Are they going to bring the adverts now?

50:16What makes Snowflake unique?

50:19In one word--

50:20Yeah, the adverts.

50:20--architecture.

50:21Cool.

50:22So part one done.

50:23Part one done.

50:24Snowflake's architecture is--

50:25How do you feel?

50:25--focussed of centralized storage for

50:27virtually unlimited amounts of structure--

50:28I hate to be honest, but this early bit is

50:30always a bit--

50:31--multiply unimpressed.

50:31Hate to be honest.

50:32Yeah, yeah.

50:33--for running multiple workloads without

50:34resource contention.

50:35Cloud services--

50:36They have to get this done in that way,

50:36right?

50:37--automate common administration, security,

50:39and database tasks in a cloud-agnostic

50:41layer

50:42to deliver a consistent experience across

50:44cloud regions and providers.

50:45--sort of key concerns--

50:46Which I think was great.

50:48I think that part was--

50:49--with a fabulous interlapse orchestra.

50:50--that was good.

50:51Welcome back to the stage, Kate Disglover.

50:52And I think it was--

50:55It's mainly just, yeah, like I said, we've

50:58tried to keep the volume up and our volume

51:00down.

51:00And I think sometimes it helped.

51:03But give us feedback.

51:04We're doing this tomorrow again for DevZa

51:06Desk.

51:06For those of you who missed the pre-show--

51:08We'll be back at it.

51:08--and Pat Hazel, your host--

51:09Please do join us again.

51:10--for all the amazing content that you will

51:12have over the next three days.

51:13I'll probably do some post keynote chat to

51:17get some feedback on the roadmap.

51:21[BELL RINGING]

51:24[CHEERING]

51:34Traitor.

51:38[LAUGHTER]

51:43It's Bits and Bytes time.

51:45There is so much exciting content coming up

51:47.

51:47Here to share--

51:48I still am.

51:48--what we can expect on day two is one of

51:50our fabulous field reporters.

51:52Data fam, welcome to Tableau Conferences.

51:56My name is Sia from Mannheim, Germany, and

51:59I live on a chess field.

52:00For me, personally, having data champions

52:03are a great way to accelerate the

52:04transformation

52:05of organizations--

52:06You left me.

52:06--to become data-driven and helping with

52:09establishing a data culture.

52:10And if you want to know more about data

52:12champions--

52:12It's a little head nod.

52:13--and data culture--

52:14It was not bad.

52:14--make sure to tune into the building and

52:16data culture channel--

52:17It's like the Carlton dance from Fresh

52:18Prince of Bel-Air.

52:19--Stephanie Richardson talked about why we

52:21need more data leaders--

52:22[LAUGHTER]

52:23You nearly could.

52:24--all hear about--

52:25Just need a jump and you're done.

52:26--brought these analysts back from their

52:28breaking point and turned them into data

52:30believers on the Analytics for Everyone

52:32channel.

52:33Find more information about these--

52:35I can hear you.

52:36--on the What to Watch page of the TC20ish

52:38event website.

52:40And that is the update from Mannheim's

52:41chess field.

52:42I'm Sia.

52:43Enjoy the rest of this event.

52:45Now, here to share a forecast of our day

52:47three activities,

52:49please welcome my field reporter--

52:50All right.

52:51I think this is me.

52:51This is me.

52:52This is probably my phone.

52:53Hold on.

52:54I'm Rahim.

52:55And thank you for joining us at Tableau

52:57Conferences.

52:58Community-led sessions are the heart of our

53:02conference.

53:03That is where you get to hear the amazing

53:05stories--

53:06Ah, zoom and hijack.

53:07--of how data is being utilized--

53:08--lized.

53:09--in every aspect of our day-to-day lives.

53:11Host of Data Diaries.

53:14Five-time Zen master Anya Ahern will lead

53:18our public sector experts

53:20in a discussion of how government agencies

53:24have had to accelerate their data

53:26strategies

53:27in light of the challenges--

53:28--increased operational speed and

53:39efficiency at scale--

53:42Hey.

53:43--and championed their digital

53:44transformation journey.

53:45Someone type--

53:46Find more information--

53:47--banana hammock--

53:48--at this session--

53:48--if you can hear me.

53:48--on the What to Watch page of the CC20

53:51event website.

53:52[LAUGHTER]

53:52I'm really happy you just got a cascaded

53:54banana hammock.

53:55It was great talking to all of you data

53:56people.

53:57This is definitely--

53:58Enjoy the Tableau Conference 2020.

54:00Traditionally, we would all be gathered in

54:04Las Vegas--

54:04OK, here we go.

54:05Here we go.

54:05--but 2020 had different plans.

54:06It's going to happen.

54:07There's a lag, so--

54:08So we were forced to find a new hotel and

54:10venue partner for the Tableau Conference.

54:12No.

54:12Nothing.

54:13Damn.

54:13That's when we stumbled across the perfect

54:15location partner--

54:16[LAUGHTER]

54:17--Shelter Inn Staycation Resorts.

54:19Says you don't know how to have it.

54:20Enjoy their destination reel.

54:22Didn't work.

54:23Shelter Inn Staycation Resorts takes--

54:25Oh, did I?

54:26--a place like home--

54:26OK, cool.

54:27--to the next level.

54:27Maybe just a really good lip reading.

54:29--to your curb edge.

54:30OK, I'm back.

54:30It's the number one choice for hometown

54:32guests everywhere.

54:32Cool, cool, cool, cool, cool, cool.

54:33Each property comes equipped with family

54:35style--

54:36What was I saying?

54:36Alexander, to answer your question--

54:38--home school facilities--

54:39--we did, we don't anymore.

54:40We worked-- Tim works in Fashion Lab.

54:42I work for the City Hall Group.

54:44This is like the shortened version

54:47of what I went through earlier.

54:48Yeah, exactly.

54:49Consider our staff--

54:50TLDR.

54:51And I basically said, Radish should do the

54:53Carlton Arts.

54:53I think what happened is when I changed my

54:56head to the Zinn

54:57Hijack, the AUGA channel, and still look

54:59for my BS.

54:59So I had to let them learn, check your

55:03audio

55:04before the stream.

55:04Our field reporters are always on hand--

55:06Clearly, see, I'm learning as we go.

55:07--to give us a closer look.

55:07Ohana Hammock.

55:08Watch this.

55:08Ha ha.

55:09Amazing.

55:09Thanks, Tom.

55:10And thank you for taking the time out of

55:11your day

55:12to join us at Tablo Conference.

55:1210 out of 10.

55:13Very good, Mark.

55:13Very good.

55:14Nice flex there, though.

55:15Nice flex to this little tablo.

55:17Just like, yeah!

55:18--the first three partners' solutions pages

55:19.

55:19Just in case--

55:20Meet the experts, engage live, and ask

55:22questions.

55:23We have our solutions that can help you do

55:25even more--

55:25I was going to say, apparently the Tablo

55:26stream might be down,

55:27but I think we will swap that around when

55:29Francois comes on stage.

55:30Tablo's biz job--

55:31Tablo stream is down.

55:32--when every day--

55:32As in, like, as in, they can't hear.

55:34--with casual fighting.

55:35I don't know.

55:35Give us some audio level feedback.

55:36Oh, no.

55:36No, it's fixed.

55:37It's fixed.

55:38You guys share the tag.

55:41What was I going to say?

55:42So what do we do now?

55:44So Tim still works at the Information Lab.

55:46He's a consultant there, consultant trainer

55:48based--

55:48we both live in Essex, which is in England.

55:51But Tim's based in London.

55:54I will be based in Manchester.

55:55I work for City Football Group, who

55:58own 10 football clubs around the world,

55:59including Manchester City.

56:00In football intelligence, so working with

56:04data

56:04to impact on-field performance, we

56:06are the long-term thinkers in a short-term

56:08world.

56:08I am so proud.

56:09That's my new catchphrase for what we do.

56:12That's my baby.

56:13But yeah.

56:15Cool.

56:17I think I heard data.

56:18No.

56:21Excellent.

56:21That was data.

56:22It reminds me of what I might be going

56:23through in a club.

56:24I'm dead.

56:25[LAUGHTER]

56:26From good relationships--

56:27Yes, but Tim's expecting.

56:28--have great results.

56:28When is the actual due date?

56:29I'm not expecting.

56:30--and bring new things to life.

56:31Yeah, you have to be afraid.

56:32My fiance is expecting.

56:33Now, let's take a moment to acknowledge

56:36one of our fabulous sponsors--

56:37Exciting.

56:38--that make this broadcast possible.

56:40Any moment now.

56:41[VIDEO PLAYBACK]

56:41Thousands of companies, including McKesson

56:43--

56:43Hopefully not any moment now.

56:44--Instagram, Square--

56:45Not right now.

56:46Right, guys, we're going to close the

56:47stream.

56:47The team is off.

56:48--scale and productivity gains utilizing

56:51the Snowflake Cloud

56:52Data Platform.

56:53Snowflake has over one exabyte of data

56:55under management,

56:56and hundreds of thousands of users

56:57execute hundreds of millions of workloads

56:59every day.

57:00Does anyone-- again, Snowflake's one of

57:04these things.

57:04I get it.

57:05It's sort of-- oh, here we go.

57:07Who cares?

57:07Let's go keynote time.

57:08[CLAPPING]

57:10We need music.

57:10Hi, everyone.

57:11I'm delighted to be here with you

57:13in this incredible community.

57:15In a year unlike any other, one thing hasn

57:20't changed.

57:21We still wake up each and every day--

57:24Delmo will come back to that question after

57:26the session.

57:27--thinking about how we can help people see

57:28and understand

57:29data.

57:29This is what drives our innovation.

57:33[LAUGHTER]

57:33Stories like those we've just heard today,

57:36stories from all of you.

57:37We'll come back to that.

57:38Because data improves organizations,

57:41our communities, and our lives.

57:44And this past year, we've accelerated

57:48our pace of innovation.

57:49We've delivered a lot of new features in

57:52Tableau,

57:53new features like our new data modeling

57:56capabilities

57:58that make analyzing complex data--

57:59Data model, the thing that everyone thinks

58:01they understand--

58:02--metrics--

58:02--ish.

58:02--that help you keep track--

58:04I think I understand that.

58:04--of the key numbers--

58:05And then I'd fuse that up, everyone.

58:06--in your data.

58:06Yeah.

58:07And we've expanded Tableau prep to enable

58:10you to write to any database.

58:12That's key.

58:13So you can use our data prep capabilities

58:15for any use case.

58:17Plus, we delivered--

58:19Total analytics--

58:19--animations and buffer--

58:20--ubiquity.

58:21--calculations.

58:21Yeah, not Postgres 12, though.

58:23Even dynamic parameters.

58:25Not compatible with Postgres 12, I think,

58:26by the way.

58:26With more than 200 features delivered--

58:29A bug.

58:29--in the last 12 months, Tableau remains

58:33the broadest

58:34and the deepest analytics platform on the

58:37market.

58:37Hmm.

58:38A platform--

58:39Interesting way of defining it.

58:39--that people love to use--

58:40Broadest and deepest.

58:41--that combines visual analytics--

58:43It's a platform.

58:43--data prep--

58:44Well, we talked about this like two years

58:45ago.

58:46--storytelling and collaboration.

58:47Everyone's a platform that's easy to get

58:49started and scale,

58:51no matter where your data is stored--

58:53Yeah.

58:53--or where you want to deploy it--

58:55Come compute.

58:55--on premises or in the cloud.

58:57Depth of product in each section.

58:58And it's supported by all of you--

59:00It was broad-beam.

59:01--the broadest, most passionate--

59:03Multimedia.

59:03--community on the planet.

59:05Yeah.

59:05Yeah.

59:06Mult--

59:06Today--

59:07Yeah, multi--

59:07--I'm going to share with you--

59:08Multiplatform.

59:08--how we're extending our platform forward

59:11in new and exciting ways.

59:13As Adam mentioned earlier, in these unique

59:17times,

59:18adaptability is a critical competence.

59:20So close.

59:21Agility was my buzzword.

59:24Oh, the stream's paused.

59:26Oh, sh--

59:26Yeah, I've got to freeze.

59:28I've got to freeze.

59:29No!

59:29--a analytics platform that empowers

59:33everyone--

59:34The stream pauses every so often.

59:36--provides you with a complete picture,

59:38and it gives you speed and agility.

59:40Yeah.

59:40Because after all, data is a team sport.

59:44And data is--

59:46Yeah, you've got some agility.

59:46--the most powerful when it's in the hands

59:49of everyone.

59:50Just a bit.

59:50So you can use data to make better

59:53decisions faster,

59:54easily share organization-wide.

59:58We're working to make Tableau even more

60:00personal,

60:01more relevant, and more engaging.

60:04Yeah, you're skipping a bit.

60:05It's not a statement, yeah.

60:05Ready wherever and whenever people need

60:08insights.

60:09Now, fasten your seat belts.

60:12Our senior vice president--

60:13I think this is-- could everyone just tune

60:14in for this bit?

60:15--and self-defense data geek, Ellie Fields

60:17--

60:17We could use YouTube, and we should be fine

60:18.

60:18--will show you what's coming next to

60:19empower everyone with data.

60:21Time for YouTube channel.

60:22Ellie, since we can't do fist bumps this

60:25year,

60:25I'll throw the ball over to you.

60:27Ellie Fields.

60:28I'm going to throw the pineapple over to

60:31you to kick off the demo.

60:32You ready?

60:33Thank you, Francois.

60:36Yeah.

60:37Oh, this is nice.

60:39We all know how important it is to build a

60:40data culture.

60:41In a strong data culture, data becomes part

60:44of the business flow.

60:45People are able to find insights and data

60:48and regularly share them with one another.

60:49We're pleased to announce new capabilities

60:52to help you build a data culture.

60:55First, how you can stay on top of your data

60:57.

60:57Tableau's already the home of all kinds of

60:59business insight.

61:01Tableau's already the home of all kinds of

61:02business insight.

61:03Of course, Tableau can send you email, and

61:05that kind of works.

61:06But like many of you, I'm often out and

61:09about.

61:09I'm not always checking Tableau or checking

61:11email.

61:11These subtitles are bad.

61:12But I am on my phone, and I'm always on

61:14Slack.

61:15I'm happy to announce that we're bringing

61:18Tableau to Slack.

61:20Oh, yes.

61:21Now you can put your data front and center,

61:23right with your most important

61:24conversations.

61:25This is still Andre's app.

61:26Yes.

61:26And you'll get notifications about your

61:28data just like any Slack application.

61:29What about the other platforms?

61:30What about Teams?

61:31It looks like I just got an alert about the

61:33error rate in our service.

61:34Right here in Slack, I can click into the

61:37notification

61:38and see the image of the alert so I can see

61:40why it fired.

61:40This is literally Andre's little app if he

61:42's been Sherlocked.

61:42Or I can click to go to the live dashboard

61:45in Tableau Mobile.

61:46What better way to build a data culture

61:50than to get data right into the flow of

61:53everyday work?

61:54Now, let me move over to my laptop.

61:59When I'm in Tableau in the browser,

62:01Everyone comment your favorite features and

62:03thoughts into the chat.

62:04Lots of notifications.

62:05Metrics.

62:05I see a completely revamped notification

62:08center.

62:08I see a new button.

62:09Not only is it information rich, but it's

62:11got all my important changes,

62:13including the alert that just fired and a

62:15view of common sharing.

62:16Oh, notification center.

62:17For some, I can take action right in the

62:20pane.

62:20I like to refresh and extract.

62:22But if they're actually useful, I can go

62:24into the dashboard to learn more.

62:25These notifications help me stay on top of

62:29everything in my day.

62:30The thing is, I quite like it.

62:31Subscriptions, alerts, shares, comments.

62:33Yeah, because I think one place they'll be

62:35in your favorite channel.

62:37Whether that's Slack, email, another

62:37business system or right, Tableau.

62:38If you want people to start using Tableau

62:39as a platform to engage,

62:41you need to have a bit of familiarity.

62:44And their notifications does tick that box.

62:46But I don't have Tableau desktop on the

62:48machine.

62:49The Tilt server, terrible for the Inflation

62:51Hub server.

62:51For us, maybe a little bit better.

62:53Well, we want to give you the best of Table

62:55au.

62:55Completely in the browser, no desktop

62:57required.

62:58Next year, you'll have an end-to-end

63:01browser experience.

63:03So your users can analyze data anywhere.

63:06Browser.

63:06I've just built a new dashboard right in

63:10the browser.

63:10And it's got all kinds of powerful

63:12analytics.

63:13Here we go.

63:14I'm seeing what I couldn't do in the

63:15browser.

63:16One note, it's going to be one note.

63:17And look at those sweet animations.

63:21It's probably using React.

63:22The problem is I'm still not quite done.

63:25How do I make this right until it's ready

63:26to share?

63:26If there's a dev in the chat, please

63:28confirm or deny.

63:29Well, we're adding personal spaces to Table

63:34au.

63:35Yeah.

63:35Permissioning for notifications, yeah.

63:37Personal spaces, yeah.

63:37This is a place to save things until I'm

63:39ready to share them.

63:40Wait.

63:42For users that don't have desktop or just

63:43want to be able to access their work

63:45anywhere,

63:45this gives you all your work right inside

63:48Tableau server or Tableau online.

63:50I'm going to kill the subtitles because I

63:51don't need that.

63:52It's a safe place where you can explore,

63:54create, and share.

63:54I think leave them just because if we talk

63:56and then you get the gist at least.

63:58Fine.

63:58And Braden, keeping unfinished work out of

63:59projects and searches means less clutter on

64:01your server.

64:02Keeping things private until they're ready

64:05to share.

64:05Come on.

64:06Imagine that.

64:06This kind of governance is critical to

64:09support a data culture.

64:09And personal spaces just dumping stuff.

64:11Now I also need to make a few quick changes

64:14to this very popular already published

64:16dashboard.

64:16Yeah, this is how do you curate it?

64:17Yeah, because it's personal space.

64:19I'm going to add marks to labels.

64:21One of the great new analytical features we

64:23added last year.

64:24And it looks great.

64:25It looks perfect.

64:26It's exactly the way I want.

64:28Or at least allow like automated printing.

64:35That's the worst.

64:36But if this happens to you, never fear.

64:40We've got you.

64:40We're adding autosave to Tableau.

64:45Yeah.

64:45Yeah, sandboxing was lapsed.

64:46If I refresh the page, I'll now see draft.

64:50I can go back to where I was or discard the

64:53changes.

64:53Ooh, draft.

64:55All save in Tableau because we all deserve

64:57a second chance.

64:58You and I remember a certain goal about

65:00this.

65:00A complete end to end browser experience

65:04requires advanced analytical features like

65:06actions and

65:07sets.

65:07But it also means users need a great

65:09experience.

65:10The same place to save work and autosave

65:13for when those mistakes happen.

65:15I will stand up.

65:16Tableau is providing market leading

65:18flexibility across desktop and the web.

65:21Now, it's great that we have these new

65:24insights.

65:26But if I never share them, do they really

65:28exist?

65:28If a dashboard falls in the woods and it

65:31doesn't share an insight--

65:33If a tree falls in the forest.

65:35In a thriving data culture, your Tableau

65:38environment is flooded with content.

65:39You can try to organize it by project, but

65:42it's hard for people to find things.

65:44So they build wikis or email--

65:45Oh, this is it.

65:46What if I had a place I could put all of

65:50them?

65:50Today, we're introducing a better way for

65:54everyone in the data culture to curate and

65:56share their knowledge.

65:57We call it collections.

65:59Collections are new places where you can

66:02group related content together from

66:04anywhere on

66:05your server.

66:05If projects are like--

66:07Amazing.

66:07Finally.

66:08Collections are like a place.

66:10Love it.

66:11You can remix your data however you want,

66:13just like you create a running playlist.

66:15This is a collection about a cross team

66:17project addressing a surge in demand.

66:20I've added some dashboards and some metrics

66:22showing KPIs.

66:23This is going to be super useful for like--

66:26Instead of creating a dashboard that allows

66:29you to link to key dashboard, key things.

66:31Just write this up.

66:33Yeah.

66:33And put it in the collection.

66:34Yeah.

66:35Oh, this is going to be amazing.

66:36You can build a collection for anything.

66:40Mark's going to get in the comments about

66:41permissioning again.

66:42For weekly reports, cross team initiatives,

66:43for onboarding so your new team members

66:45have

66:45a great starting point.

66:46In the future, we'll make collections more

66:50visual and let you embed visualizations and

66:53ask data right in the paint so people can

66:57ask a new question.

66:59Now, this is what a data culture should

67:00look like.

67:01You and your team, always up to date.

67:03Data and analytics, wherever you need them.

67:07And experiences for people at all skill

67:09levels.

67:10Interrogate this.

67:10To use data right in their workflow.

67:12The stuff you want to pause in.

67:13Thank you.

67:14It's always the stuff they're not talking

67:15about.

67:15Yeah.

67:16At conference, you could take a picture and

67:21look.

67:22Here's like, rewind the stream.

67:23You can actually pause.

67:24We can't pause, but everyone else can pause

67:25.

67:25A personal space that houses all of your

67:27analysis.

67:28Collections to easily--

67:30Caption said a better way of people can

67:32carry and ship their knowledge.

67:33And analytics that automatically reach

67:35people wherever they are.

67:36That was a great--

67:37That's the power and flexibility to deliver

67:40self-service analytics at scale.

67:42But we must balance self-service with

67:46governance.

67:48This means empowering people while

67:51maintaining the right control and security.

67:53Mark actually did take a screenshot of it.

67:55Fantastic.

67:55After all, the insights we gain from data

67:58are only as trustworthy as the data itself.

68:01And that's why trust is at the core of the

68:04Tableau platform.

68:06Enabling you to meet your governance,

68:09security, and--

68:09Yeah, permissions and collections.

68:11I think it would just work the same, I

68:12guess.

68:12While delivering self-service analytics--

68:14The thing is, though--

68:15It's where Red Level Security is going to

68:16be.

68:17It's going to be a--

68:18This is it.

68:19--directly into the Tableau platform to

68:21help you trust your data.

68:23I'm working for a large consumer goods

68:24company.

68:25From data prep to data catalog.

68:26Data certification to query federation.

68:30The Tableau data management capabilities

68:33help you discover all of your data.

68:36See how it's being used.

68:38View its lineage and impact analysis.

68:40And because it's integrated into the

68:43analytics platform,

68:45you're able to bring value to all of your

68:48users.

68:49You need some love.

68:50Yeah.

68:50IT--

68:50Hey, maybe the management solves that.

68:52Here's your segue.

68:53--all of the data is being used, how it's

68:55being transformed.

68:57They can curate and add definitions to the

68:59data.

69:00And end users have the confidence that they

69:03're using the right data for their

69:05analysis so they can trust their decisions.

69:09Right.

69:09Everyone benefits from data management.

69:12To show you what's next in data management,

69:16please welcome one of our star innovators,

69:19Marky Kitama.

69:20Marky, the pineapple is all yours.

69:24I've actually got to chat with her next

69:26week.

69:27Thanks, Manswah.

69:27Name drop.

69:30As Adam mentioned earlier today--

69:32Chatting prep.

69:32--data is more important than ever before.

69:35And as a Black woman, I'm proud of the

69:38steps that we're taking in partnership

69:40with all of you to fight racial inequity

69:44with data.

69:45No matter what kind of data you're working

69:48with, it's got to be clean.

69:50We want to give you the flexibility to

69:52prepare your data from anywhere,

69:55whether it's on the desktop or on the web.

69:59Oh.

70:00I'm so excited to introduce Tableau prep

70:03for the browser.

70:05Here's a flow that cleans sales data.

70:07All the data connectivity options,

70:10everything you know and love,

70:12100% of the features are all available

70:16right here.

70:17Measly 16 gig RAM.

70:18This flow currently has two outputs.

70:20The first is a published data source.

70:23So users offering this is the only product

70:25where I think you need--

70:26The second one outputs to a database.

70:29One of our most requested and new--

70:31How big is your big data?

70:33It's currently writing out to a SQL Server

70:35table.

70:36This gives people the flexibility to use

70:41this clean data inside and outside the

70:45Tableau platform.

70:46You know what you could do with this, right

70:47?

70:47Like work in the browser.

70:48Tableau prep in the browser brings the full

70:50power of self-service data preparation to

70:54everyone.

70:54Apple Pencil, Tableau prep, boom.

70:56To prepare data anywhere for any use case.

70:58Prep ubiquity.

71:00Now this flow has been operationalized

71:02using prep conductor.

71:04And right now it's refreshing once a day.

71:06Everything in this flow automatically shows

71:11up in the Tableau catalog.

71:12From here you can see the SQL Server table

71:17that we were outputting from our flow.

71:18You can also see that there are 93 work

71:21books that depend on this flow.

71:24We're working on making things even more

71:27automatic.

71:28Keeping data like this fresh is business

71:30critical.

71:31But sometimes flows run into problems.

71:33And today admins and data stewards are no

71:36longer there.

71:37I think this is going to be smoother

71:39because of the engine it's built on.

71:40This was built from the ground up to be on

71:42the web.

71:42People building visits, reviewing dash

71:45boards, use this data and need this

71:48information as well.

71:49So they can trust the data.

71:50Whereas desktop is the harder challenge to

71:52transition from desktop anyway.

71:54That we're introducing automated data

71:56quality warnings.

71:58Let me show you.

71:58At the top of the Tableau catalog I can go

72:01ahead and add a refresh monitor.

72:04We'll select prep flow monitoring.

72:07Select the type of data quality warning.

72:09And paste in the message I'd like my users

72:12to see.

72:12And now when this flow fails a data quality

72:15warning will be generated automatically.

72:18Just like everything else in the catalog

72:21these automatically generated data quality

72:24warnings

72:25flow all the way to visits and dashboards.

72:27So all users can see that.

72:29If I enable that today I get that for the

72:32on 20% of my data sources.

72:35If you've got prep conductor though.

72:37I know that's what I'm saying.

72:38And from data details we can see the

72:41warning.

72:4120% of data sources would have an error.

72:45With features like automated data quality

72:48warnings Tableau catalog embeds trust and

72:51visibility.

72:52Yeah, yeah, I know I can this is also part

72:54of the data management.

72:55I think this all is apart from prep and

72:57browser.

72:57Of course.

72:58But there's another element to trust.

72:59Imagine if prep and browser is surely can't

73:02be.

73:02No, no, no.

73:03And you want to trust your users with the

73:06right data.

73:07What you want is a central location to

73:09define, debug, and manage data access.

73:13And I'm happy to announce that our next big

73:16leap innovation in the data management

73:18space

73:19is centralized row level security.

73:21Here we are back in Tableau server.

73:25We're introducing a new concept to manage

73:27data access and security policies.

73:29Here are the tables that make up a sales

73:32data model.

73:33Right now it contains info about sales

73:37transactions,

73:38sales agents, and the accounts they're

73:40responsible for.

73:42Security policies.

73:42Now I want to protect this sensitive data

73:44and make sure people only see data about

73:47their

73:47accounts and we can do that using security

73:50policies.

73:51At the moment, there are two security

73:54policies. We'll delve a little deeper into

73:56this one.

73:56Then you show me the calculation.

73:57Defining and defining security policies is

74:00easy.

74:01On the right, I can see the security policy

74:04expressed as a calculation.

74:06And it's evaluated for every row.

74:09Now as it's currently defined, executives

74:12will be able to see all the data.

74:14Sales agents will only be able to see the

74:17rows associated with the accounts.

74:17It's quite funny.

74:18I was speaking to a dev last month and I

74:20was ranting about how there should be just

74:22a brand

74:22new interface for managing data.

74:24Here it is.

74:26There you go.

74:27We just said about row level security, we

74:31're having some love.

74:32But I don't like the use of this function

74:36because it's not flexible enough.

74:40I can't hit that typing in member of.

74:42With centralized role of security, checking

74:46your work is visual and direct.

74:48You can verify exactly who's going to see

74:52what data.

74:52For example, a sales agent like Alexis can

74:57only see three rows.

74:58Because that's the data associated with her

75:00accounts.

75:01Whereas a manager like Donnell can see over

75:05a thousand rows.

75:07Because those are the rows associated with

75:08his team.

75:10We know that visibility is important to you

75:13.

75:13People in your organization should be able

75:16to easily see which data sets have security

75:18policies applied to them.

75:20Why in prep?

75:21We bring that information right to you.

75:23Here's the lineage information for this

75:26data.

75:27And from here, I can see that a security

75:29policy exists for two tables.

75:31Here they are.

75:32Powerful.

75:34With Tableau data management, you get a

75:37complete picture of all your data.

75:40Now, today was just a sneak peek.

75:43There's much more to come.

75:44Yeah, Mark, I reckon they'll let you do

75:46hard-coded data management by group.

75:48Because most people, everyone in this chat,

75:51please use groups.

75:53Don't use people.

75:53Awesome.

75:53That was really great.

75:54Yes.

75:55Yeah.

75:56I love prep builder in your browser.

75:59Thanks, manager.

76:00The Tableau catalog, it just keeps getting

76:02more and more powerful.

76:04And centralized role of security, a feature

77:49that many of you have asked for, will make

76:09securing data easier and more flexible than

76:13ever.

76:13That's something that people have asked for

76:14all the time.

76:15To be adaptable, you also need speed and

76:18agility.

76:18And then off it.

76:19And this has been the hallmark of Tableau.

76:22Helping people get insights more quickly,

76:26staying in the flow of analysis, and making

76:28it easy for anyone to ask questions of

76:31their data.

76:32It's more than just visualizations.

76:35It's about enabling deeper thinking, giving

76:38people the freedom to explore data without

76:41limits.

76:42That's why people love using Tableau.

76:45And we're always looking to make the

76:47complex simple, providing powerful

76:50capabilities while

76:52making it easily accessible to more people.

76:54Well, we're about to make a giant leap

76:58forward by bringing Einstein Discovery to

77:01Tableau.

77:03Einstein Discovery is a core AI technology

77:06within Salesforce.

77:07It helps you find statistical patterns in

77:10your data that can reveal key insights

77:13automatically.

77:14It helps with predictions such as

77:17likelihood to buy.

77:18It's like an obligatory Salesforce feature.

77:21I don't know.

77:22I'm not sold on Einstein.

77:23But I'm guessing it helps people who use

77:25Salesforce.

77:26At all times.

77:27I think the amount of effort is being able

77:28to explain what it is.

77:29Will be integrated across the Tableau

77:32products in dashboards and calculations.

77:34It took me a while to understand what

77:36Einstein is.

77:36To show you these new capabilities in

77:39action, please welcome one of our newest

77:41members of

77:42our data family, Bobby Bill.

77:44Don't make me explain it.

77:45Bobby.

77:45Because I probably can't.

77:46But I think I know what it is.

77:47Is coming your way.

77:48Thank you, Francois.

77:52Hello, Tableau community.

77:55I'm Bobby with the Einstein Discovery team.

77:59Focused on AI power, data discovery and

78:01predictions.

78:03You sure?

78:04This is my very first Tableau conference.

78:07Everyone in the comments.

78:09Green screen or not green screen comment.

78:10Go.

78:11Power of Einstein Discovery to all of Table

78:15au.

78:15Give it a look.

78:17As a product manager, I love analyzing data

78:20.

78:20Especially customer adoption data.

78:24Because that tells me whether or not I'm

78:26building useful products.

78:28That are solving customer problems.

78:30In this example, customer adoption

78:33dashboard.

78:34Which is similar to one that I look at on a

78:36frequent basis.

78:37I can see the count of new users this month

78:41.

78:41Along with a breakdown of views by various

78:44product areas.

78:46I'm interested in learning what's driving

78:50users to come back on a more frequent basis

78:53.

78:53So that I can make data driven decisions on

78:56adoption.

78:56Team green screen.

78:58Let's see what Einstein has to tell me

79:00about the likelihood of users staying

79:02engaged.

79:03Introducing the Einstein Discovery

79:06extension.

79:08Oh no.

79:08I can see the average predicted engagement

79:12rate in real time.

79:14I mean it's the extension.

79:15It means you don't have to have it if you

79:16don't want it.

79:17It's not in your face.

79:18But how is it driving this?

79:20Is it the age or problem like?

79:22Okay so...

79:22It's a black box.

79:24Show me how you've done this.

79:26I can see what's driving that prediction.

79:28And it's all based on my historical data.

79:31I can see that users...

79:34But this is it right?

79:34So it's the age old question of do you care

79:37about the answer or do you care about why?

79:41Most people just care about the answer

79:42right?

79:43It's just give me the answer.

79:44Until it's being used to tell them what to

79:46do.

79:46Then it starts to be why.

79:47That's having a negative impact on the

79:49overall user engagement.

79:50Yeah.

79:51It's moving the needle away from using bad

80:08data to inform us.

79:57So we're using a black box to inform.

80:00Right here, LionSign has given me some top

80:05improvement options.

80:06And I can see that if I can get users to

80:09take the basic and intermediate training,

80:11they will be more likely to stay engaged.

80:15I'll be sure to share this insight with my

80:18team so that we can start moving the

80:20adoption needle.

80:20And because this is inside my Tableau

80:24dashboard, it's also interactive.

80:26That's the only thing.

80:27At least the Tableau dashboard I know has

80:29been built.

80:30I get a new...

80:31No, no, no.

80:32On the fly.

80:33If you want to, you can pick it apart.

80:35I'm guessing you can go back along the

80:38weeds and see the model behind it.

80:40Inside Einstein Discovery with absolutely

80:43no code.

80:44I wonder if this is just explained data but

80:48relabeled as Einstein?

80:49No.

80:50Explained data is still something.

80:51So how are they different then?

80:54And click and Einstein is deep, deep linked

80:57into Salesforce.

80:57But the power of predictions are not just

80:59for dash.

81:00Explained data.

81:01We've integrated Einstein Discovery across

81:03all of Tableau, including the Tableau

81:06calculation engine.

81:07And it's as simple as creating a calculated

81:11field and using the new Einstein Discovery

81:14connection.

81:15New action interface.

81:17Hello.

81:18I'm interested in seeing the average

81:20predicted user engagement.

81:21I think just for the add-ons, because that

81:23was also Python and...

81:25Right, right.

81:25No, just for that though.

81:26I'll start by dragging the highest training

81:28completed field into my row shelf.

81:30I did that for maps as well.

81:31Because Einstein Discovery does row level

81:33predictions, I'll include the row ID in my

81:35details.

81:36And last, I created a calculated predicted

81:39user engagement field.

81:41Because I don't have this persisted in my

81:43data source.

81:43And when I click and drag that onto my

81:45column shelf, I get real-time dynamic...

81:50Row ID.

81:51Powered by Einstein Discovery coming from

81:54my Salesforce...

81:54It did, but he's forced it to all be bars.

81:57And just like that, I was able to slice my

81:59data...

82:00Yeah, I looked at the bottom left

82:01immediately.

82:01Right, I was going to say.

82:03And it's clear that the users that take the

82:05intermediate and advanced level trainings

82:07are more likely to stay engaged.

82:10But what if your company's like mine and

82:15uses Tableau Prep

82:16to clean and prepare your data sources

82:18prior to building your visualizations?

82:21Well, that's exactly why we've integrated

82:23Einstein Discovery directly into Tableau

82:26Prep.

82:26And it's all done with Google Lakes.

82:28I think you have to say it, but it almost

82:30feels like a mouthful from a hackathon.

82:32Like, how come it is?

82:34Where I'm joining my user-adoptioned books

82:36with training usage.

82:37Sorry, like...

82:38To insert predictions...

82:39It just feels like they've bungled it in.

82:41I can click and add a new prediction node.

82:43There's no sort of origin story for it

82:44within the Tableau world, right?

82:46I can select my prediction from Einstein

82:48Discovery.

82:49I'll use the predictive engagement score.

82:51And now I can bulk score all my data.

82:58What?

82:59And look, there's my new prediction call.

83:01I'll answer that question in a second,

83:02Alexander.

83:03And it's got predictions.

83:04I'll let this thing and I'll explain what's

83:05going on.

83:05And remember the top improvements and

83:07predictors I showed you in the dashboard?

83:09You'll get those written directly to the

83:11data source as well.

83:13Simply check these boxes and choose the

83:16number of predictors and improvements

83:18you want included.

83:19It's that simple.

83:22And when I run my...

83:25I like the language of top predictors

83:27rather than just the answer.

83:29Yeah, exactly.

83:30And this data source is ready to be

83:32consumed.

83:33That way your fellow dashboard authors don

83:37't have to worry about setting up an

83:38integration

83:39to get the full power of Einstein Discovery

83:41.

83:41Prep does all the work for you.

83:44This is super powerful.

83:47By integrating Einstein Discovery across

83:51all of tab...

83:52For Salesforce users.

83:53Not only can you see what happened with

83:55your data,

83:56but you'll get a view into the future with

83:58predictions.

83:58I can't wait to see how you use this in

84:01your organization.

84:03Back to you, Francois.

84:05Boom.

84:07That is such a cool demo.

84:09Can't wait for this community.

84:10Yeah, okay.

84:10You're right.

84:11Green screen.

84:11Yeah.

84:13He didn't move enough and then he moved and

84:15he's like, yep, that's green screen.

84:16Right inside of Tableau.

84:18And everyone will be able to use the power

84:20of data science and bring it to even more

84:23people.

84:23Einstein Discovery is just one of the many

84:28powerful capabilities

84:29that are part of Einstein Analytics.

84:32Einstein Analytics is the native experience

84:35embedded right into Salesforce.

84:38It brings actionable analytics directly in

84:41the flow of the Salesforce users.

84:44It solves that swivel chair problem and it

84:47delivers insights where people work.

84:49That's a new one.

84:50Swivel chair problem.

84:51And as Adam mentioned earlier, our teams

84:53have come together under one roof.

84:55And now our products are coming together

84:58too.

84:59It's lasting.

85:00Well, I'm pleased to announce that we're

85:03bringing together Tableau and Einstein

85:05Analytics.

85:06We're going to combine the best of both

85:10products to deliver an even broader and

85:13deeper...

85:13But you would have just started that thing

85:14again.

85:15And we'll be doing this by building deep

85:17integrations between Tableau and Einstein

85:19Analytics.

85:20It might be live.

85:21We'll make sure we deliver a seamless

85:23experience for our joint customers.

85:26The reason is because I saw a picture of

85:28Francois wearing a different shirt.

85:29And this means that data in Einstein

85:31Analytics will be available on Tableau.

85:33On Twitter when I was tweeting about the

85:34stream.

85:35So you can benefit from secure and native

85:36access to your Salesforce data.

85:39Einstein Analytics will be able to leverage

85:42data from Tableau.

85:43So you have common, well-curated data

85:46anywhere it needs to be accessed.

85:48Our data prep capabilities will be able to

85:52write...

85:52Again, this is just one of these things

85:54that's...

85:54...and Einstein Analytics.

85:55It's marked into a crowd of people who have

85:57Salesforce and might want Tableau.

86:00And it's now giving them more reason to

86:02swap and get more benefit.

86:04So you have to create the content only once

86:07and consume it anywhere.

86:08So guessing the first five rows of

86:10conference.

86:11Or embed it in your apps.

86:12Now as part of these changes, we're also

86:16going to change the name of Einstein

86:18Analytics to Tableau CRM.

86:21First five rows of conference.

86:22Tableau CRM is the best solution to deliver

86:26contextual and actionable analytics to

86:29every Salesforce user.

86:30Tableau CRM.

86:31We're very excited about this journey.

86:33It won't happen overnight.

86:36And so we remain very committed to your

86:38success.

86:39Wait.

86:40We will retain and build on the current

86:42capabilities you depend on.

86:44Even as we innovate and expand going

86:47forward.

86:48Now as we look beyond our unified analytics

86:52vision,

86:52it's been extremely exciting to go deep

86:55into the Salesforce platform.

86:57The innovations working across the company

87:00on ways that we can accelerate our mission.

87:03So there's so much technology across Sales

87:06force that we can use to help you analyze

87:10and take action on your data.

87:12For example, we're working with MuleSoft.

87:16The number one.

87:16That's why you call that random segment at

87:18the end there.

87:18This is an unlock.

87:21This MuleSoft integration.

87:23MuleSoft can connect to hundreds of sources

87:25of data from applications to APIs.

87:29And all of those sources will be just one

87:31click away for you to use in Tableau.

87:34Yes.

87:34We're also working with Datarama to help

87:38you analyze all of your marketing data much

87:41more easily with Tableau.

87:42Datarama is a powerful platform for

87:46marketers to integrate and harmonize

87:49marketing.

87:49That Tableau plus Einstein equals Tableau

87:52CRM.

87:53Can you explain a bit better?

87:54So you can easily explore that data live in

87:56Tableau.

87:58It definitely sounded like a rebrand of all

87:59of Tableau.

88:00Even more integrations with all of the

88:02Salesforce products to unlock the full

88:05value of the Salesforce Customer 360.

88:08We're working on improved connectivity.

88:10I don't like this pitch about Salesforce

88:13Customer 360.

88:14Because what this means is they're not

88:17going to be investing energy in sort of

88:19bettering Tableau's integration to things

88:22like Cloud Platforms.

88:22We're accelerating innovation with Sales

88:24force.

88:24Because Salesforce also doesn't integrate

88:26with other Cloud platforms.

88:27Like AWS.

88:28No, but I'm talking about focus.

88:30I'm not talking about what they do or don't

88:31do.

88:31The focus of what they can spend time into.

88:33And we need to empower everyone.

88:35The dev team is bigger now.

88:36That's where we're going.

88:38Everyone who doesn't use Salesforce.

88:39I couldn't be more excited about the road

88:41ahead.

88:41Thank you very much.

88:42I'd say for Tableau's maybe, I don't know,

88:46I don't have a number.

88:47I don't think it's the majority of the

88:48customers.

88:48So excited on behalf of our customers.

88:50We're innovating as fast as we can to help

88:54all of you be more adaptable.

88:56And to help even more people see and

88:58understand data.

89:00I'm just as excited about this community.

89:03And what I know we're going to achieve

89:05together.

89:06There's no one I'd rather have on my side

89:08in trying times than the Tableau community.

89:11And now with Einstein Analytics and the

89:13entire Salesforce Trailblazer community.

89:15Our data fam just got a whole lot bigger.

89:18We have a great Tableau conference for you.

89:22And there's no ish about that.

89:24It's so great to be here with our customers

89:26, our partners, and our sponsors who helped

89:28us figure out how to bring TC to this

89:30virtual experience, including our diamond

89:33sponsor Snowflake.

89:34Up next, our CTO, Andrew Beers, and Netflix

89:38co-founder Mark Randolph,

89:40are going to discuss data's role in driving

89:42impact in the 21st century.

89:44But before we move on to that, we have a

89:46special treat for you.

89:48I'm really excited to introduce an

89:50incredible guest who's joining TC this week

89:53.

89:54He'll be joining a powerful fireside chat

89:56later.

89:57John.

89:57He's going to be giving us a special

89:59performance later this week.

90:00And now he's going to perform just for you.

90:03The legend.

90:04I know you know him.

90:04The legend that is.

90:05Emmy, Grammy, Oscar, and Tony award-winning

90:08singer-songwriter John Legend.

90:11Thank you to Adam for introducing me.

90:16Thank you to my new friend at Tableau for

90:21bringing us all together.

90:24I mean, John Legend should be a Tableau fan

90:29anyway, given that he

90:30used to work for BCG before he made it in

90:33the music biz.

90:34Look at that flex with his Grammys behind

90:39him.

90:39Okay, pretty much.

90:52We can let John sing.

90:54Should we sing along?

90:56Got the lyrics.

90:58I love the sub-tosers again.

91:17It's kind of funny.

91:22Like a drunken thing.

91:23Yeah, I reckon this is prerecorded, Sam.

91:30100%.

91:31I mean, it would kind of suck.

91:34Sorry about that, John.

91:38Anyway, talk to us about Data.

91:40I wonder why John Legend's like for the

91:48people.

91:50Used to work for BCG, so he's got a

91:52background in analytics, I guess.

91:54Yeah, but I don't know.

91:59It's about to do some inside bass for about

92:10a second.

92:11Oh, and this is done, right?

92:13Sure.

92:15I'm guessing he's gonna do one song and

92:19then he goes to swap to adverts.

92:20True, true.

92:21Let's take a pause.

92:24Everyone's left the live stream and come to

92:26our stream instead.

92:27Maybe they're looking for some live

92:30feedback.

92:31We're going up in VOCAM, which is, you know

92:28, I've gone down.

92:35I won't report live on this.

92:37Yeah, go on.

92:40Let's talk.

92:40My insert speed is 60 megs.

92:43So the secret to the setup is actually not

92:46Ravi's internet connection.

92:48It doesn't matter how good Ravi's internet

92:52connection is.

92:54He's just got to be able to hold a zoom

92:55call, which he can do, which is fine.

92:58So the actual whole horsework is being done

93:01on my side.

93:02And I'll just attach my webcam.

93:04So I have my desktop PC over there, which

93:11is streaming basically OBS.

93:16I can probably share my screen.

93:19Don't mess with the system, man.

93:21Yeah, let me move OBS so people can see

93:24what I'm actually working with on my side.

93:26Here you go.

93:28So this is OBS.

93:29Basically, this little green lightning is

93:32pushing out.

93:33And you can see the bandwidth.

93:34It just needs two meg of bandwidth up to

93:37basically keep the stream alive and

93:39everything going.

93:41Yeah.

93:45This is Pat Heisel at Tremlite Studios,

93:47sponsored by Snowflake.

93:48Super simple.

93:48And joining us next will be Tableau's CTO,

93:52Andrew Beer.

93:5261 down.

93:53It's the up-value that really matters.

93:56I've just set the stream to not go above 8%

93:59of my total upload bandwidth.

94:02That's how you make sure you have a smooth

94:03stream and it doesn't cut out.

94:05And then YouTube and OBS do the hard work

94:08of figuring out how to deliver high quality

94:10audio.

94:11We have a brand new Caffeinated partner

94:14that promises to keep you motivated.

94:16I give you Visual Aid.

94:18[VIDEO PLAYBACK]

94:19- Do you want to know the secret to monster

94:21data conversion?

94:22It helps to drink the company Kool Aid.

94:24- Properly grainy.

94:26- Exactly.

94:27- But if I switch to mine, it's a lot

94:28higher quality.

94:29- The energy drink visualizers rely on to

94:32turn epic levels into epic skills in the

94:32blink of an eye.

94:33- I think that's also the machine I'm using

94:34.

94:34- Yeah, I didn't properly switch between

94:36these views.

94:37- This is the beverage that gives you

94:39leverage with a jolt of caffeination to

94:41boost your illustrations.

94:43Visual Aid, for your daily data soda quote.

94:47- This is funny.

94:48- Now in an affordable portable recyclable

94:51receptacle.

94:52- I'm sure you're going to get this

94:55mentioned by someone.

94:56- Tableau Zen Masters have been selected

94:57through their mastery of the product,

94:57a willingness to share knowledge, and a

94:59desire to help us improve the

95:01fabulous solutions of tomorrow.

95:02- I ended up sending it back to Amazon

95:04because I didn't use any sort of camera

95:06that needed that capture card.

95:08So the graphics card actually that I have

95:11on my PC has something called Envink,

95:13which can decode and encode video.

95:16- Hey, Zen's about to get a shout, man.

95:17- Oh, sorry, Ravi.

95:19Oh, okay.

95:20- All hail Zen Masters.

95:21- All hail Zen Masters.

95:23- This is almost like a missing persons

95:25list.

95:26- All hail Zen Masters.

95:27- If you see these people, please contact

95:32the authority.

95:33- They should have done like a video call

95:34out, like, "Hey, I'm so and so, and we are

95:37..."

95:37- "I'm so glad we did it. I'm so glad we

95:39did it."

95:40- It's like they used like Animoto or some

95:43...

95:43- Crave blood.

95:45- Crave blood.

95:46- Oh, that's not Crave blood.

95:49- That's cool.

95:49- Josh.

95:50- Josh is incredible.

95:51- Kelly Hall of Famer.

95:53- Ken.

95:54- Two Kens.

95:55- Ken and Kevin.

95:56- Two Flarges.

95:57- They've got the surname spelled wrong for

96:00Flawledge.

96:01- Yeah.

96:01- Lindsay.

96:02- All guides.

96:03- Lorna.

96:03- Good old Lorna.

96:04- Leek.

96:05- I don't know why we're all calling them

96:07out.

96:08- You're saying...

96:08- Yeah, right. Exactly.

96:09- There's so many. Wowzers.

96:13- Yeah, it's 31.

96:16- Where are you, Ravi?

96:16- Hey.

96:16- I could actually...

96:17- Yeah, I think it's... Oh, wow, that's a

96:21big face.

96:21- Sarah. Good old Sarah. Simon.

96:25- There you go.

96:25- Ironviz finalist, Simon, as well.

96:28- Yeah. Looking forward to Ironviz. We're

96:31not going to stream that one. You can just

96:33watch

96:33that on your own.

96:34- Have we met a Zen Masters?

96:36- It's time for a little...

96:37- I am hosting a stream with one right now.

96:39- Funny business.

96:40- Yeah, we're quite fortunate at the

96:43Information Lab to have quite a few of the

96:45Zen Masters

96:46in one place. So I definitely have met a

96:48lot of Zen Masters. I also talk to them

96:50sort of

96:50outside of the community. So yeah, it's...

96:53I think Alexander generally didn't know you

96:56were a Zen Master.

96:57- It's fine.

96:58- How dare he? How dare he not know, Ravi?

97:01- It's fine. It's not a...

97:02- Would you like me to...

97:03- I'd love Tableau because it allows me to

97:06ask me to...

97:07- No, no. It's... No, I don't... I'm just

97:09wearing it.

97:10- I love Tableau because I can see and

97:11understand my data.

97:12- I think I'd wear this for the first day

97:13anyway.

97:13- I fell in love with Tableau as a customer

97:15because it originally took a six-week

97:18project

97:18and turned it into a three-hour project.

97:20- It's an interesting initiative. I think

97:21it's like...

97:22- And I've been a fangirl ever since.

97:23- It just feels like...

97:24- I think people always look at it as some

97:26sort of... I mean, I'm not one, so I can't

97:28say this. Whereas you can come back and

97:30defend in some way. But I think they are

97:33lots of Zen masters all around the world

97:35who are never recognized in their own

97:37organizations

97:38and stuff like that. So basically, it's

97:40just...

97:41- There is something magical about Tableau

97:44in the incredible user community that you

97:47all have developed and the amount of

97:48resources that are available. It's so rare

97:51in the state

97:51government we don't have the ability to

97:54hire outside consultants or assistants.

97:57- It kind of works out.

97:58- No.

97:58- We do have to be in-house and in-home.

97:59- Yeah, no, no. It's completely in jest,

98:02Alexander. Tim is joking. But yeah, no, it

98:04was an

98:05honor to be one. I genuinely didn't think I

98:07'd ever become one to the extent that I

98:10actually started reaching out to Devs

98:11directly because I was like, the thing I

98:13want the most

98:13from this is to get to know the people that

98:15build Tableau.

98:15- To be a data person?

98:16- Yeah. So yeah, it was, yes, an honor to

98:19be one.

98:20- When I found Tableau, it just... I couldn

98:22't hold it anymore.

98:23- It is a large list. It does grow every

98:25year and change every year.

98:26- It pretty much came out as a true data

98:28person.

98:28- Very cool. Very cool.

98:30- Really, it's hard not to when you've got

98:32a tool that's just so fun to use.

98:34- People think that on the surface level,

98:37it's basically Excel, but it's not even

98:41close

98:41to the same thing.

98:42- I love Tableau because it really provides

98:45a platform where it's endless hours and

98:48hours

98:48so that people can talk and exchange ideas

98:51and...

98:51- What have we got next then? Have we got

98:53Netflix? Shall we cut the feeds? I don't

98:57know

98:57whether it's going to continue listening to

98:59Netflix, man.

99:00- ...be using it from law enforcement

99:02agencies to private sector companies and

99:04NASA and

99:05government.

99:06- What is this akin to? I'm trying to think

99:07. Do we actually ever have this...

99:08- Do we actually have this company?

99:09- Yeah, they usually get a customer on

99:10stage.

99:11- I love Tableau, but they're writing just

99:13people's names.

99:14- Yeah, they do it early on. Yeah.

99:15- That's why, yeah, yeah.

99:16- So they do the data story and the CO and

99:19then they get a customer in the middle.

99:21- What's up Tableau community? We're the

99:21Fabulous Evil Ox Orchestra.

99:21- Then we then finish with some product

99:23roadmap stuff.

99:24- And we're here to put you in the interop.

99:24Here we go.

99:25- Let me reduce the volume of the stream.

99:27- Yeah, for sure. Yeah, and then I think

99:31the fireside chat is just a continuation,

99:34just to finish the morning off because this

99:37is... For the US folks, this is the morning

99:40of

99:40conference, right?

99:41- Yeah, exactly.

99:42- So this is going to be replayed in EMEA

99:44from 9 till 12 tomorrow.

99:45- Yeah, so it's interesting. The conference

99:50, it feels weird. Conference is live, you

99:53know?

99:53All the sessions are playing out on all the

99:55different broadcast channels and I'm

99:57probably

99:58going to go have dinner and then go to bed.

99:59- Yeah, yeah, exactly. Exactly.

100:01- And then wake up tomorrow and see what

100:03everyone's raving about. I think devs@desk

100:06is the next

100:06thing. And I want the 2020.4 announcement

100:10beta to drop so then I can go and actually

100:13start recording videos. That's all I'm here

100:17for.

100:18- So shall we finish up then for tonight?

100:20Let's do a quick recap. What do we hear? So

100:23we

100:23heard Adam talking about this year with CO

100:26VID and the diversity. I thought you did a

100:29really

100:29good job there just going through all those

100:32. It's quite a difficult topic, quite a

100:33current

100:34topic. But I think Tableau is staying out

100:36there still in a really succinct and clear

100:38way with some great speakers, I thought.

100:40- Yeah, absolutely.

100:41- It was great. And then following Adam, we

100:45had Mr. Francois, Elie, Moraki and the

100:48Salesforce

100:49guy.

100:49- Bill. Bill.

100:52- Bill?

100:52- Someone Brill. No, someone Brill. I can't

100:55remember.

100:55- Yeah. Joe Brill?

100:56- That's really bad. I'm really sorry if

100:57you're watching the stream back. Yeah, just

101:00I guess

101:01we spend a lot of time with the other devs

101:03so we're probably very familiar with them.

101:05- Yeah, absolutely. So...

101:10- So yeah, they went through desktop and

101:12browsers, parcel spaces and collections,

101:15which I'm very

101:15excited for. Really looking forward to

101:16collections.

101:17- Yeah.

101:17- I think... And then yeah.

101:21- Bobby Bro. Bobby Bro. Thank you, Adam.

101:22- That's what we've got for this evening.

101:26We'll be back tomorrow.

101:27- Devs at desk.

101:28- Devs at desk, quarter to five. We'll

101:32probably smooth this out tomorrow.

101:35- Two promises for tomorrow. I will learn

101:37how to audio mix.

101:38- Let's take away number one. I've actually

101:42literally had cues on the chat telling me

101:44when the audio levels aren't great. I need

101:46to find a way...

101:46- Bobby Brill. That's the guy's name. Bobby

101:48Brill.

101:49- Of cueing audio myself. So yeah, we'll

101:51definitely get the audio better and we'll

101:53be a lot smoother.

101:53But otherwise, you know, thank you for

101:55being in our audience today. It's been

101:57really, really good.

101:58- Yeah.

101:58- I think we managed to figure out this

102:00live stream thing finally, minus audio hicc

102:03ups. So yeah.

102:04- Excellent. No, thank you all for joining.

102:07Come join us for Devs at Desk. What we'll

102:09do

102:09after Devs at Desk, given it's a half an

102:11hour session, is just chat. Let's talk

102:14about the

102:14features, talk about the stuff that was

102:16mentioned today in the roadmap as well in a

102:18bit more detail.

102:18Maybe we'll do half an hour watching and

102:20listening to that and then we'll do some

102:23reaction afterwards.

102:25- Yeah.

102:25- Sound good?

102:26- Absolutely. Sounds excellent. Right.