Dreamforce reaction

0:00Hey, it's Tim here. In today's video, we're

0:01doing something slightly different. I've

0:03got my headphones on because we're going to

0:04be doing a reaction to a video from Dream

0:07force. Now Dreamforce is the annual

0:10conference at Salesforce. And of course,

0:12this year, like last year has been sort of

0:14different. So there's been an online

0:15presence for our Dreamforce is known to be

0:18one of the largest conferences in the world

0:19. If you've been to a tablet conference, and

0:21you think that's big, wait till you see

0:22Dreamforce Dreamforce is just on another

0:25level in terms of scale. And in terms of

0:27the kind of people, the different products

0:29that

0:29are covered there, it's just something else

0:32. And of course, now that Tableau is part of

0:33the Salesforce family, it's actually quite

0:35important now that we start paying

0:37attention to the keynotes that are

0:39delivered at Salesforce. Because of course,

0:41that is now the new home for Tableau. So

0:43what I thought I'd do this time round is I

0:45do a live reaction to the Dreamforce

0:48keynote, essentially for Tableau, if that

0:50makes sense. But what I want to do is start

0:53on the Salesforce plus page, because this

0:55is actually where all the content is being

0:57hosted. Salesforce plus was announced

0:59earlier in the

0:59year, basically, whenever you hear a plus

1:02on a product, it's normally the streaming

1:04version of that particular product, I

1:06personally hate it, I don't know why

1:08everyone decided to do it. Maybe it's off

1:10to Disney plus, people, people just sort of

1:12took to that, I don't know, who knows. But

1:14nonetheless, we're here. And so what you

1:16can do is you can go to the Dreamforce page

1:18, if I just click on that here, and actually

1:20goes directly to the content just about

1:23Dreamforce in 2021. And if you go down,

1:25there's a whole bunch of different content.

1:27And actually, while we're here, it's kind

1:28of interesting.

1:29And Dreamforce is, is a huge event. So what

1:32you have to do is you have to help people

1:34channel their time and energy. And you have

1:37to make sure that people kind of find the

1:38content they need to watch. But also, there

1:41is a big presence after the event. So you

1:43also want to make it easy for people to

1:45browse the content that's been shared

1:47during the conference. And the way they're

1:49doing is they're announcing episodes sort

1:51of throughout the whole entire conference,

1:53just to string out the content, it makes a

1:54lot of sense. But you can see here, they're

1:56split by roles. And this is kind of

1:58interesting. So the

1:59key roles they have ourselves, service

2:01marketeers, commerce, it admins, developers

2:04, architects, and partners, pretty

2:06interesting that trailblazers sort of from

2:08all of these except for service marketeers

2:10and commerce. And I don't know why that is,

2:12that's obviously a very deliberate decision

2:14. For some reason, if you know, let me know.

2:16And then you've got it by topic. And I

2:18found this actually the most interesting.

2:20So you've got the best of Dreamforce, which

2:21is like the super playlist, then you've got

2:23slack, obviously, Salesforce acquired slack

2:26. So slack has its own sort of topic here.

2:28And that

2:28makes sense, because it's very much its own

2:30product. And then you have a customer 360.

2:33Now, if you know anything about Salesforce,

2:35they've been drumming on about the customer

2:37360 for a long while I first noticed that

2:39roughly two years ago, I'm seeing adverts

2:41on TV and how and even on YouTube channels

2:45that I follow. So it's quite a big thing.

2:46They're putting a lot of energy into it.

2:48Data integration, customer success, small

2:51business, financial services, health and

2:54life sciences, public sector, comms and

2:56media, retail consumer goods,

2:58salesforce.org, and other industry. So

3:00these are clearly sort of industry vertical

3:02s that they're pitching, and they're

3:04pitching sort of general capability. So I'd

3:06expect a lot of Tableau content to be in

3:08the data and integration space. So if I go

3:10click into that, let's just hit this button

3:13here, you can actually see there's a

3:15separate playlist. And the episodes are

3:17sort of labeled in here in order of how

3:19they appeared. So Tableau AI, essentially,

3:22when Salesforce acquired Tableau, what they

3:24've done is they've taken the Tableau brand,

3:27and applied it to most

3:28of the analytical features in Einstein with

3:31a Tableau brand. So Tableau AI is

3:33essentially what used to be called Einstein

3:35Analytics. So a lot of the content here

3:38will say Tableau AI, it will seem new to

3:40lots of Tableau users. But that's because

3:43it's just it's a repackaging of all the

3:45products. And they've been various blog

3:47posts throughout the year to sort of

3:48highlight this as well. So there's a bit of

3:50MuleSoft, which is another key sort of part

3:52of the Salesforce world, unlocking insights

3:55with Tableau. This is probably the first

3:57reinforce

3:57where Salesforce really want to introduce

3:59Tableau to its customers. I think from this

4:02point onwards, you really start to see

4:04Tableau being sold alongside other Sales

4:06force product in one package. So you're

4:08going to see lots more content from Sales

4:10force about Tableau that's going to feel

4:13like it's being sort of pinched to a very

4:15new audience. And that makes a lot of sense

4:17. You've got a couple more Tableau videos.

4:21But there's a lot of sort of different

4:22technologies here. So you see MuleSoft, you

4:25see Tableau AI, Einstein Analytics, you

4:27see a lot about Tableau. And we've actually

4:29got what I'd consider the keynote here from

4:31the Tableau perspective. So that's actually

4:33what I'm going to react to. But if I just

4:35scroll down, you can see there's lots of

4:37great stuff in him, Slack First Analytics.

4:40This is a capability across Salesforce and

4:43Tableau, Tableau and AWS. And so I'd expect

4:47this sort of playlist to sort of play out a

4:48little bit more over time. But in essence,

4:50if I go back, and we go for that didn't

4:54work, if I go back, and we go just to

4:57the Explore More option here on the top

4:59page, this actually gives us a playlist of

5:01all the key content in the order that it

5:03was released. So this kind of shows you the

5:05chronology of Dreamforce online at least.

5:07And so we want to go to episode I think it

5:10's Yeah, Episode 29, which came out a few

5:12days ago. Mark Nelson basically was leading

5:15this keynote. So if I click onto this, I

5:18think I have to click the play button to go

5:19to the page. And yeah, here we have it

5:21Tableau, unleash the power of your data,

5:24starring Rob Burse, VP and head of global B

5:262B

5:27ecommerce, Kellogg company, so he's

5:30obviously a customer, Philip Cooper, Vice

5:33President, product Tableau Salesforce,

5:37David Lu senior PM at Tableau, Mark Nelson,

5:40CEO, of course, of knee Avni Vadar, I think

5:44director of product management at Sales

5:47force. Arlene Weber, director of product

5:50marketing at Tableau, and Francois Arzun

5:52stad, we all know Francois, we don't have to

5:54say who that is CPA and TPD.

5:57At Tableau, okay. And so there's a bunch of

5:59other content. So what I'm going to do is I

6:01'm going to react to this in sort of the raw

6:04form. I haven't watched this. I've been

6:06involved in a conversation about it, but I

6:08haven't actually watched the content. I

6:11read some notes about sort of what was

6:13covered in the in the in the conference. So

6:15I want to get stuck in and just just see

6:17what we saw we take of this. So I'm going

6:19to be pretty open and honest, I think a key

6:22role as a you know, Zen master sometimes is

6:24to be sort of a

6:25critical friend in that sense. So I'm going

6:28to try and be as pragmatic and as honest as

6:30I can be from what I hear. And we're going

6:33to sort of reflect on it at the end as well

6:35. So let's get started. And yeah, let's see

6:38what we find out.

6:44Okay, so right out of the bat, I think I do

6:47have to say one thing, which is, it's, it's

6:50so interesting how Salesforce marketing,

6:53like pitches, the ecosystem of Salesforce,

6:56it's always done in this sort of very

6:59foresty and woody environments, you always

7:02have trees, you've got this Einstein guy,

7:04there's always animals involved, even the

7:06Salesforce spring releases, those are all

7:08pitched around wildlife, there's this sort

7:10of sort of analogy that I painting almost

7:13around nature and you know, being in the

7:15wild, and it's sort of an interesting thing

7:17, because if you've ever seen a Salesforce

7:19interface, it's far from those kind of

7:21scenes, it's actually very clunky, because

7:23it's essentially lots of things that are

7:26plugged together. So I find that

7:28interesting. And it's been interesting to

7:29see that sort of migrate over to Tableau,

7:32we've seen Tableau staff start to, you know

7:35, their emails have changed, their slide

7:37decks have changed. And so there's a lot of

7:39Salesforce looking stuff in this, and we

7:41should expect this at conference at Tableau

7:43conference as well, Tableau does have its

7:45own identity. And it's sort of, I think,

7:47desperately trying to hold on to it as much

7:50of it as much as it can, because that's

7:52what most Tableau users are familiar with

7:54historically. But nonetheless, I think the

7:56Salesforce sort of the Salesforce identity

7:59is a strong one. And I think it's just a

8:02matter of time before we we kind of lose

8:04what we use to know is the Tableau identity

8:06instead of image. So yeah, let's get stuck

8:08into this and see see a bit more.

8:10Alright, it's time for everyone's favorite

8:19moment. It's the forward looking statement.

8:21Today we'll be sharing some exciting news

8:23and announcements. Please make all of your

8:26purchasing decisions based on commercially

8:28available products, right?

8:33Okay, so this is exactly what I mean. I

8:35mean, you're coming out into a stage and

8:37look at look, just look at how much effort

8:39has gone into the stage. This is, this isn

8:41't sort of accidental, the stage is very

8:43much set in this way. And this is important

8:45for two reasons. They know this is being

8:47filmed. So all of this also forms a

8:49backdrop. And it does try and paint an

8:52image about I think the not the not the

8:55ethos, but just the aura around the product

8:58, how you should feel around the product,

9:00this is sort of their message. You should

9:02feel calm

9:03out one with nature, natural, all these

9:05colors, green, yellow, blue, these are all

9:08very sort of natural colors. And that's

9:10what they try and associate themselves with

9:12. And that's a very deliberate ploy. I don't

9:15know why I don't know too much about that

9:17in the past. But all I know from my

9:19experience in design is that is a very

9:21important sort of thing they're going for

9:24here. It's so deliberate, you can't sort of

9:26ignore it. So let's play on anyway.

9:31Is Mark. Hello, everyone. Welcome to the

9:35Tableau keynote at Dreamforce 2021. We're

9:38so excited to have you join us today, those

9:40of you in person here in San Francisco, and

9:42all of you online around the world. Okay,

9:45so this is interesting Dreamforce actually

9:47did have a few people at conference. That's

9:50interesting, because the Tableau conference

9:52is not in person, it's all virtual. And

9:55that's an interesting, it's interesting

9:57that Dreamforce is sooner. And there's, I

9:59believe there's a lot of sort of

10:01difficulty with, you know, in America

10:01around vaccinations and the resurgence of

10:01the the variant that originated in India.

10:01And but it's interesting that some people

10:01have actually made it to the real event.

10:01And you can see them here on video. I

10:01wonder if those people are like a select

10:01few people that have sort of been granted

10:01access. So it's not the hundreds of

10:01thousands, but it's more like the thousands

10:01of people that have made it to the event,

10:01just to

10:31give it a bit of atmosphere. And I will

10:32also say one small thing. Mark Nelson's l

10:35avalier mic is absolutely huge. lavalier m

10:38ics are supposed to be small. And I think

10:40they're outside, you can kind of see there

10:43's a little bit of wind if you look at the

10:45brushes, there's there's wind blowing

10:47around. And I think he's got a massive sort

10:49of windshield on his lavalier mic, but you

10:52can also actually get these lavalier mics

10:55that eclipse that go underneath your top.

10:58So the lavalier mike could have been placed

11:00slightly differently to just just not make

11:02it as obvious as it is. And it's not doing

11:04a good job of actually blocking the wind. I

11:06can hear that just in the audio. Maybe I'm

11:08being picky, but nonetheless, I mean, can't

11:11help it. I mean, it's the CEO of Tableau,

11:13you could have at least given them like a

11:15decent lav mic anyway, nevermind.

11:17I'm Mark Nelson, President and CEO of Table

11:20au. And today we have some exciting

11:22innovations to share with you. But first, I

11:24wanted to say thank you. Thank you to our

11:26new listeners. Thank you for tuning in

11:28today. And thank you to our existing

11:30customers. Thank you for your business. And

11:33thank you for the feedback that make our

11:34products better every release.

11:38That's an interesting opening statement.

11:40And he first started by saying thank you to

11:42the new watches. So very much acknowledging

11:45the new audience. And then obviously not

11:47forgetting the heritage of Tableau thanking

11:50past customers. I think that's an important

11:52sentiment or maybe touching that later. Let

11:55's watch the rest and see if it comes up

11:57again. But just wanted to sort of highlight

11:59that.

12:00We're working in an all digital work from

12:02anywhere world. Data has never been more

12:04important because every digital

12:06transformation is a data transformation. As

12:09you go digital, you get new data that helps

12:12you see your business and your customers in

12:14an entirely new way. Data is the lifeblood

12:17of every organization. And here at Tableau,

12:20our mission has always been to help people

12:22see and understand data.

12:25Because people are at the center of our

12:27mission, we help organizations of every

12:30size and in every industry establish a data

12:33culture. And it's interesting.

12:38We, I think the choice of word is very

12:41smart there. And why don't know what you

12:45heard when when you had that, but we help

12:48is a very important one help doesn't mean

12:52that you get them there. It doesn't mean

12:55that you do it for them help. It's like one

12:59one one part of a bigger picture. And so

13:03yeah, let's just see. Let's see what else

13:04he says

13:05in establishing a data culture. There are

13:07two pieces, the technology piece and the

13:09people piece. Well, the best parts of my

13:12job is I get to talk to customers and

13:13leaders who have established great data

13:16cultures all the time. And I hear some main

13:19themes in those conversations on what they

13:21want from the technology that helps them

13:23establish those data cultures.

13:24OK, yeah. First is to bring analytics to

13:27the people. You have to have it. So you

13:29have data and analytics where people work

13:32every day, and that means embedding

13:34analytics into the applications where they

13:37work. Right. Second is to make it easy for

13:40people to get to the answers that they want

13:42. That means people of all technical skills

13:45have to easily get to the answers and

13:47insights that they need.

13:49It also means being powerful tools like A.I

13:51. and M.L. to everyone without making them

13:53become data scientists. If you can bring

13:55those intelligent insights to your users,

13:58your tool will be loved by people. And that

14:02love of the tool is key to adoption and

14:04utilization to truly establish a data

14:07culture.

14:08If you're going to have all of your users

14:10using data, it has to be trusted and

14:12governed. That's both for the security of

14:14your data and to know that the insights

14:16that people are getting from that data are

14:19accurate and can be trusted. And last but

14:21certainly not least, is to have

14:23collaboration built in because

14:25collaboration is the key to getting those

14:27insights and answers across your entire

14:29organization and truly establishing that

14:31data culture.

14:33This is really cool, because, well, I'm

14:36maybe jumping ahead there, but I'm

14:38interested in this because it's put on here

14:41. It's interesting, really interesting. They

14:45are blocks for a data driven organization.

14:48And there's sort of a level of layers

14:50behind this embedded in business apps. In

14:54that image, you can see Salesforce and you

14:56can see something embedded inside of Sales

14:58force. I don't think it's actually a Tableau

15:00dashboard. It might be a Tableau dashboard,

15:02but it's too small

15:03to really make it out. Easy and smart.

15:05Einstein there, there's a little hint

15:07towards Einstein Analytics. Loved by people

15:10talking about the love for Tableau desktop,

15:13Tableau public and sort of the existing

15:15sort of heritage around Tableau. Its users

15:18commonly talk about how much they enjoy

15:20using it. Trust and governments, this is

15:22pointing at Tableau server, and then

15:25collaborative, hinting to words, Slack here

15:29in that screenshot, but what they're really

15:30talking about is the ability for people to

15:32sort of engage

15:33in discussions with data recently with

15:34Slack, but on Tableau server and commenting

15:37and all those capabilities, as well as

15:39inside of Salesforce. Einstein has also

15:41allowed people to sort of do the same kind

15:43of thing. So it's interesting that these

15:47are the sort of five pillars that they talk

15:50about for the data driven organization. So

15:52let's see what else Mark has to say.

15:55Now I know that's a lot to take in and a

15:57lot to keep in your head. So the good news

15:59is no matter where you are on your data

16:01culture journey, Tableau can help. And

16:04today we're going to talk about three steps

16:06to get started to truly unleash the power

16:08of your data. The first of these steps is

16:11speed. We'll talk about how to get started

16:13quickly and discover insights fast. The

16:16next is intelligence. How to get

16:17intelligence infused throughout your

16:19business and to make data driven decisions.

16:22And last but not least is collaborate.

16:24And how you collaborate on all your amazing

16:26insights to build a strong data culture. So

16:28get started on this journey and talk about

16:30our first step. I'm going to bring out

16:31Francois to talk about speed.

16:33Great. Francois is the chief product

16:36marketing officer. Yeah, I think Francois'

16:39role is the role of the...

16:42The first step in building a data culture

16:44is helping everyone make better decisions

16:47faster. Because speed matters. Getting data

16:50into the right hands of the right people at

16:53the right time is the difference between

16:56thriving and barely surviving. But there

16:59are a lot of challenges to getting that

17:02data to the people.

17:04Getting speed is really, really hard. As we

17:06're accelerating the digital transformation,

17:09we're also accelerating the data

17:10transformation. The average enterprise has

17:14over 900 applications generating data.

17:18There's data everywhere. And with all of

17:21that data, we're drowning in data and

17:24lacking in insights. It could take months

17:27to get value from all of that data.

17:31What we want is to unlock all of that data

17:33and make it easily accessible to everyone.

17:36It's not a data explosion, it's data chaos.

17:38And this is where Tableau comes in. We

17:41provide built in connectors to all of your

17:43applications.

17:45Whether that data is sitting in databases

17:47or applications, on premises or in the

17:50cloud, we can help you get to that data

17:53quickly.

17:55So this is interesting. What they've chosen

17:57on this list is very interesting. Because

18:00in the past, it's not been this. In the

18:02past, it's been this sort of very old, like

18:06laggard databases like Microsoft SQL Server

18:09, you know, what is it?

18:13Redshift, all those kind of databases, you

18:15know, standard, I forget the term for them.

18:19It's not coming to me, it's coming to me.

18:21Oh, no. Anyway, just the traditional

18:24databases that you've always heard of

18:27Oracle, those kind of thing.

18:29This is interesting. Data Armor, Salesforce

18:31, Marketing Cloud, Salesforce, Salesforce C

18:34DP, Salesforce, MuleSoft, Salesforce,

18:37Commerce Cloud coming. I think Commerce

18:39Cloud is part of Salesforce. Azure,

18:41interesting, they'd call out a pretty big

18:44competitor in this sense, Microsoft.

18:47So they've picked out some of the most

18:57forward looking and freshest data sources

19:09in the industry. So it's sort of

19:15interesting.

19:16And yeah, the connectors are there. There's

19:18a little obviously caveat, those not all

19:20those connectors exist in all parts of the

19:22product, but across the tablet platform,

19:24they're generally that many connectors. And

19:27you can obviously add more with a DBC

19:29connectors, web data connectors and so on

19:31and so forth.

19:33We provide out of the box connectors to

19:35everything. And we're introducing new

19:38connectors for Salesforce data, new

19:40connectors for Marketing Cloud, Commerce

19:43Cloud, Data Rama, MuleSoft and the brand

19:46new Salesforce CDP.

19:48Tableau is the fastest way to get from data

19:51to insights for the entire Customer 360.

19:55But for those of you that live and breathe

19:58Salesforce data, well, we got something for

20:00you too.

20:02We're introducing Salesforce data pipelines

20:04. Salesforce data pipelines is the easiest

20:08and fastest way to prepare, transform and

20:10augment your Salesforce data.

20:14So this looks like an Einstein analytics

20:17sort of evolution. It feels like something

20:20that Einstein analytics was working on

20:23before. Because this visual sort of

20:26documentation, this this this sort of

20:29visual design of a product. If Tableau was

20:32doing this, it would look more like Tableau

20:34prep.

20:36If it was going to be sort of built by the

20:38same sort of group of people, but this,

20:40this looks different. This looks more akin

20:43to sort of Einstein analytics. But let's

20:45keep watching.

20:47It's built right into Salesforce. So you

20:49get the trust, the scale and the

20:51performance that you expect with Salesforce

20:53. So now all of that Salesforce data can be

20:56easily prepared and loaded directly into

20:59the trusted CRM.

21:02Okay, so now that we have access to all of

21:04this data, how do we bring it out to people

21:07, right? And Tableau is the easiest way to

21:10get data and insights. But we want to go

21:12one step further. We're bringing Tableau

21:15everywhere across the Customer 360. We're

21:19bringing it to every Salesforce cloud and

21:21every industry. We're introducing pre built

21:23dashboard starters.

21:26So something that's hitting me hard here is

21:28that, man, I am not in tune with the Sales

21:30force ecosystem language, right? And I

21:33generally know what the 360 is, I know what

21:35the sort of general tools are. But it's so

21:38interesting to hear Tableau executives

21:42talking very fluently about different parts

21:46of the Salesforce ecosystem.

21:48So Salesforce audience, you're probably

21:50completely in tune with this. If you're a

21:52trailblazer or someone who's lived and

21:54breathed Salesforce for the last few years,

21:56you're probably pretty aware of all of

21:58these parts. But as someone who, dare I say

22:02Tableau's endmaster, this is all very

22:05foreign to me.

22:06And it's not sort of what I understand a

22:08Tableau. So yeah, I'll come back to this

22:10point a little later on. But yeah, let's

22:12keep listening.

22:15So the dashboard starters help you go from

22:17data to insights and minutes. These

22:19dashboard starters provide built in best

22:22practices for your industry and for your

22:24use case. It includes key performance

22:27indicators, transformations, and pre built

22:30dashboards that help you bring your data to

22:33life.

22:35And this is really interesting because a

22:38few weeks or maybe a couple months ago,

22:41Salesforce announced they were buying a

22:44partner in the Nordics, I think I can't

22:47remember exactly. And let me see if I can

22:50try and find it. So let's try Salesforce

22:53acquires Tableau partner. Let's see if we

22:58can find it.

23:00Here we go. I think I found it. Had to

23:02search quite a bit on Google. But here we

23:04go. I think I found it. It's this

23:06particular welcome Lin Tao essay to the

23:09Tableau data fam. With Thrill, Salesforce

23:12has acquired Lin to essay a global tablet

23:13partner based in Switzerland, Switzerland,

23:16that delivers analytical analytics

23:18dashboard templates and consulting

23:20expertise in dashboard designs.

23:23Welcome to the Tableau team. Okay, so if I

23:26go and search this particular company, we

23:29probably will find something here you go.

23:34And so looking for a dashboard, they're

23:38clearly a they're clearly like a dash

23:42boarding templating kind of company. So let

23:45's see.

23:48You can kind of it looks like a shopping

23:50cart for different Yeah, they seem to have

23:53like a bunch of dashboards for different

23:55industries ready to go. And it's kind of

23:58interesting. Let's see that they have Table

24:01au, Power BI and so on and so forth. But it

24:04's probably their dashboards in the Tableau

24:06space that got most people are very

24:08interesting. So they have different sorts

24:14of build and design processes. It's kind of

24:17interesting how they're built.

24:17It's kind of interesting how they they go

24:19about it. They've got their sort of general

24:21area there. Let's see what this is. Any

24:25relational data. This is just like a

24:29marketing video. I mean, I'm in the

24:33template man like, I'm two minds about

24:36templates. templates is sort of weird. I

24:41don't know, we'll have to wait and see what

24:42they're like. But anyway, we're getting off

24:44sidetracked here. And Tableau acquired this

24:45company a few months ago.

24:46And then hey, what'd you know, there are

24:49lots of starter templates ready to go in

24:52Salesforce. I should have said Salesforce

24:55acquired that company a few months ago, but

24:56technically Salesforce is Tableau. So it

24:58was actually Tableau. But nonetheless, hey,

25:00we have some dashboards ready to go.

25:02Surprise, surprise.

25:05And we know that data is a competitive

25:07differentiator. The organizations that can

25:10utilize that data effectively, are able to

25:13generate better business outcomes and

25:16deliver better services. And nobody has

25:19unlocked data, as well as Kellogg's. Kell

25:23ogg's is truly the customer in the data

25:27transformation and in analytics.

25:29And it's my pleasure and honor to introduce

25:32Rob Burse, head of global B2B eCommerce to

25:35share you his story. Rob.

25:38Virtual fist bump. Welcome to Greenforce.

25:45Thank you very much. Pleasure to be here.

25:47That's fantastic. Tell us about your role

25:50at Kellogg's.

25:51So you heard I'm responsible for global B2B

25:53eCommerce. So it's very much an innovation

25:56role. There's a lot of things happening.

25:59But fundamentally, you know, it's all about

26:01powering the vision that we put together.

26:03We're looking to change the industry, the

26:05industry's approach to value creation,

26:07especially across the long tail of retail.

26:10This segment, you know, we feel is very

26:12important and can unlock a lot of potential

26:14for us.

26:15So we're starting with, obviously providing

26:18enterprise level analytics to thousands of

26:21retailers, so that we can collaborate

26:23digitally with them and share insights that

26:26can help power their growth from today,

26:29tomorrow and into the future.

26:30So we think it's a very, very powerful

26:31value proposition. And I'm just personally

26:34excited to see how it unfolds.

26:36I have to say, like, like, I'm gonna say

26:39this about fast moving consumer goods

26:42companies, and that is that they talk a

26:44good talk. But when having worked, I think,

26:49nearly half of my consulting life for fast

26:52moving consumer goods companies, they talk

26:56a good talk.

26:58However, when you actually get down to the

27:00detail, like if you actually boil down what

27:03's being said, and what's being done on the

27:05ground, it can look very, very different.

27:09So they are great people to have on the

27:12stage because they do very much live at

27:15this sort of frontier of data. Pretty much

27:18everything they do is data, things like

27:20running promotions, looking at things like

27:23retail price indexes around the world,

27:26things like distribution,

27:27everything around the fast moving consumer

27:30business is about sort of fine tuning costs

27:33at such a minute level, because of the

27:35scale that they operate at. So data is very

27:38much at the heart of that. So I'm

27:40absolutely great customer to have on stage.

27:43But I always say, look, you really have to

27:45pay attention to what's actually being said

27:48and what's actually been shown to evaluate

27:50for yourself whether the sort of the claims

27:53match the reality if that makes I'm not

27:55saying it's not true. I'm just saying these

28:00things, these statements can sound grand,

28:01but when you actually get down on the

28:02ground, it's it's a very, very different

28:04world. So let's just keep listening.

28:06That's incredible. So Rob, how is Kellogg's

28:08using Salesforce and Tableau to drive

28:10business outcomes for all your retailers

28:12out there?

28:13Yeah, so it's a multifaceted approach. We

28:16're trying to build a single common platform

28:19that allows us to create value across our

28:23customer base and solve ecommerce problems

28:26for the markets that we work across.

28:29That was just a masterclass in how to say

28:33something without saying anything. Okay.

28:38Yeah, let's let me instead of jumping to

28:40conclusions, let me just finish this and

28:44just see. Branswaj is basically asked, how

28:46are you doing it? Okay, let's wait and see.

28:49So, you know, in our value proposition, we

28:53're trying to find a path to create the

28:57tools that turn the lights on.

29:01You'd be surprised or maybe you won't. Many

29:03of our retailers, especially the small

29:05retailers, have no insight into how they're

29:07performing versus their peers by logging in

29:10to mykellogg.com,

29:12which is, of course, powered by Commerce

29:15Cloud, and then accessing the Tableau data

29:18powered by Einstein,

29:20we're able to provide every retailer with

29:22the ability to see how they're comparing

29:24themselves, especially their peer groups,

29:26and then also monitor their growth.

29:29That's really interesting. So when you dig

29:30down, he uses the word Tableau, but he's

29:33actually talking about Salesforce and

29:35Einstein analytics. Really key point there.

29:40As the action, some of the recommendations

29:41that we're bringing. Now, this is the

29:43interesting part. The recommendations

29:45themselves are what changes everything.

29:49We're able to now identify the most

29:51important products that represent the ideal

29:55assortment in every store,

29:57in every part of the world, no matter what

30:00store it is, size, shape, location.

30:03And from there, we can make recommendations

30:05to ensure that every store can maximize

30:08shelf revenue today, in line with consumer

30:10demand.

30:11Totally game changing, fantastically

30:13exciting.

30:14That's amazing. That's a game changer. It's

30:16speed, it's intelligence, it's

30:17collaboration all built in.

30:19Absolutely. So last question for you. Why

30:21did you choose Tableau?

30:23So I think I still stand by my statement.

30:26He said what's going on. He didn't actually

30:28say how.

30:29He said what they're using. He's talking

30:31about Einstein analytics, he's talking

30:32about Salesforce.

30:34He's talking about the outcomes and so on

30:36and so forth. And that's fine.

30:39But he didn't actually say how. What is

30:41Einstein analytics actually doing to arrive

30:43at these predictions?

30:45Einstein analytics is an off the shelf

30:47product, Salesforce. I think we know what

30:49that's involved in.

30:50It's basically the platform they log into.

30:53But what exactly is it doing?

30:56That's not really in this question. They're

30:57just basically talking about the fact that

30:59they're using it and that's it.

31:01There is no real how underneath that. But

31:03this is part of the conference.

31:05This chat from Kellogg's is not going to

31:08get on stage and tell the whole world how

31:11exactly they're using it.

31:12Because of course, it's a competitive

31:14advantage. So he has to talk about it in

31:16his cryptic ways.

31:17But I just wanted to call that out. But

31:20yeah.

31:20Clearly you're getting a lot of value. What

31:22were some of the deciding factors to

31:24choosing Tableau to help you power this

31:25transformation?

31:27Three reasons. The first is we wanted to

31:29stay on platform. We want to make sure the

31:30applications we were using played well

31:33together.

31:33And make sure that we weren't handicapping

31:35the extensibility of the platform going

31:37forward.

31:38Two is that we wanted to make sure that we

31:40had an opportunity to use speed and

31:42velocity, but have flexibility.

31:45So we have thousands, if not millions of

31:47pieces of data we wanted to consume and

31:49then test.

31:50Test with the customer to make sure that it

31:51was resonating and delivering against our

31:53promise.

31:54And then the final thing is ensuring that

31:56we're able to do all of this and make it

31:58easy to consume through a mobile device.

32:01And Tableau did all that for us.

32:03That's amazing. Interesting again, the use

32:05of Tableau.

32:06What is interesting there is those key

32:09points were the kind of things that people

32:13talk about in business and operations as

32:17being the desirable outcomes of things.

32:21So it's again Tableau and Salesforce making

32:24sure that Rob's talking points here really

32:27ring home to people.

32:29I wouldn't be surprised if Rob's talking

32:31points and sort of what he was going to say

32:33was refined a little bit to sort of touch

32:35on these things.

32:36Because he's a customer as well, so he is

32:38sort of speaking true to this phenomenon.

32:41He wouldn't be on stage speaking to it if

32:43he didn't believe he spoke to it.

32:45But the choice of words, the choice of

32:46points, that can sometimes be a

32:48collaborative thing.

32:50Amazing. Well, thank you for being a Trail

32:52blazer. Thank you for being here and sharing

32:54your story.

32:55Thank you very much. Take care. Cheers.

32:57So that was really interesting. We didn't

33:01see anything. We didn't really get the how

33:03and there you go. Off stage.

33:06Here you go, Rob at Kellogg doing these

33:08great things.

33:09Maybe there's a session that Rob does a

33:10little later on where you get hands on.

33:13At a normal Tableau conference you would

33:14get something like that where you sort of

33:16get into the deep dive and it's an hour

33:18session.

33:19So I'll try and look around and see if

33:20there's maybe a session where Rob does go

33:22into that into more detail.

33:24But again, if I was honest, it's the kind

33:26of thing that a business consultant would

33:28have turned up and said they were going to

33:30do for you prior to delivering the project.

33:32So it's nothing really sort of that

33:34surprising.

33:35But it's nice that, you know, Rob as a

33:37customer feels confident getting up and

33:39saying that this is what it is actually

33:41doing for us.

33:42It takes a lot to stand up and sort of back

33:46a product in that way.

33:49So speed, intelligence and collaboration

33:51were core to Kellogg's success.

33:54And intelligence is at the heart of Sales

33:56force and at the heart of Tableau.

33:59And I'm pleased to welcome Avni to share

34:01with you how we're bringing intelligence

34:04across the Tableau and Salesforce platform.

34:07Avni.

34:08Thank you, Francois. And welcome to all of

34:16you here.

34:17I'm so excited to talk to you about my

34:19favorite topic, intelligence.

34:21As Francois just showed us, the first step

34:23to building a data culture is giving your

34:25people insights fast.

34:27But to take your analytics to the next

34:29level, you need AI built everywhere that

34:31you work.

34:32OK, so this is a very big call out that

34:35this is what we used to call iPhone

34:39analytics, augmented analytics, business

34:41science.

34:42Tableau sort of launched a big push around

34:44this in the last year or so, and data

34:46science.

34:47So how this stuff sort of integrates with

34:49everything else. And these are sort of the

34:52talking points here.

34:53So this is good. Let's hear more.

34:55The problem is not everyone has access to

34:57AI, right? Just data scientists.

35:01Well, here at Tableau, we believe that

35:03every person in your business should have

35:05access to intelligent, actionable insights.

35:08That's why we've created a spectrum of

35:10analytics for every single person in your

35:12business, from your business users to your

35:14data scientists.

35:16Today, I want to focus on two key parts of

35:18the spectrum, though.

35:19So on the left, we have what's called

35:20augmented analytics, which is perfect for

35:23your sales and service reps who need quick

35:25insights right where they work and in the

35:27language that they speak.

35:29Then in the middle, we have what's called

35:31business science, which brings the power of

35:33data science to more people,

35:35making the people with business context

35:37equipped with more powerful insights than

35:40ever before.

35:41But you might be wondering, why is the

35:43spectrum important?

35:45This spectrum is the key for us to provide

35:47all of you here today with a unified

35:49analytics platform, or in other words, a

35:52unified view of the data across your

35:54enterprise.

35:55We want to empower more people with

35:57intelligence, whether their data lives in

35:59Tableau, the Salesforce Customer 360, or

36:02anywhere else across the enterprise.

36:04But part of the magic of Tableau is being

36:06able to show you how easy it is to use.

36:09So I'm going to bring Phil Cooper up, who's

36:11going to walk you through how you can embed

36:13intelligence in every step of your

36:14analytics journey.

36:16Over to you, Phil.

36:18This is one big relay race.

36:20They keep bringing people on, who bring

36:21people on, who bring people on.

36:23Today, to set the stage, I'm going to play

36:25the role of a brand manager, a large CPG

36:27company.

36:28And what you're going to see next is my go-

36:30to dashboard.

36:32I use this to track...

36:34I just want to say he's wearing a Tableau t

36:36-shirt.

36:37That is an original Tableau t-shirt.

36:41It's really good to see.

36:43Customer engagement across all my brands

36:44and all through their channels, uses this

36:46every day.

36:47And we built it with a startup for Sales

36:50force CDP.

36:51And what it does is it leverages the data

36:53collection and unification power of the

36:56state of sales.

36:57Interesting.

36:59So this is a Tableau dashboard.

37:02There I was thinking this is all about

37:04analytics, but this is a Tableau dashboard.

37:07I know that because that filters very much

37:08Tableau.

37:09The font Benton Sand, which is the Tableau

37:12font.

37:13This design is very, very common in Tableau

37:15worlds.

37:16These buttons, they're the default button

37:18styles.

37:19You know, a little point here, these aren't

37:21all the same size.

37:22It could have been a bit of refinement

37:23there.

37:24Could have been a bit of refinement on the

37:25spacing.

37:26I'm being pernickety here.

37:27But nonetheless, this is very much a Table

37:29au dashboard.

37:30So this is interesting.

37:31Salesforce CDP.

37:32And ultimately gives me a complete picture

37:34of all my customer touch points.

37:36Now, you heard about Francois talking about

37:39speed.

37:40And I use startups like this to deliver

37:42fast.

37:43And just today, a new project landed on my

37:45desk.

37:46And I absolutely do not have time to build

37:47from scratch.

37:48So luckily, Tableau has a way for me to get

37:50going really quickly.

37:52Francois mentioned that library of best in

37:54class dashboard templates.

37:56We have over 100 of these available today.

38:00And I can select the brand performance

38:02template to get going quickly.

38:05You'll see this.

38:06I'm going to click on this right now.

38:07This is going to be the best choice for me

38:09because KPIs that I need to analyze my

38:12business,

38:13like revenue, customer lifetime, value, and

38:15churn, and all the key dimensions.

38:17So I'm going to pause this and just go

38:18check something.

38:20See if maybe I've missed something.

38:22So dashboard status.

38:25Let's go just check this and see.

38:30Interesting.

38:31So what is interesting here is I'm trying

38:33to see, look, where is this thing?

38:37And I went to look on the website and it

38:40has these dashboard sites for Tableau

38:42Online.

38:43And it's got a few here, but it hasn't got

38:45as many as sort of a list there, over 100

38:48and something.

38:48So let me search this.

38:50Maybe I'm searching the wrong thing.

38:52Extension gallery.

38:55Here we go.

38:56Tableau extension gallery.

38:57Here we go.

38:58This is interesting.

38:59So this is what I think this page is.

39:04You can see home, dashboard extensions,

39:07dashboard starters, connectors, and

39:09datasets.

39:10Here we see dashboard extension connectors.

39:13We don't see datasets and we don't see

39:14dashboard starters.

39:16So I very much think that the extension

39:18gallery is going to be sort of augmented to

39:21have all of this.

39:23And I think this is what's technically

39:24being talked about here.

39:26So I expect to see some sort of dashboard

39:28starters announcement.

39:30And what we're seeing here is actually a

39:31beta, which is why at the very top it's

39:33sort of chopped off.

39:35The other key thing to notice here is that

39:37the SF here is someone's logged into

39:39something.

39:40So this is obviously going to be part of

39:42some sort of experience when you log in

39:44somewhere.

39:45And then you're going to be able to browse

39:46this marketplace of extensions and then

39:48pull them into your server.

39:50So I think that's what's going on here.

39:52Glad we found that.

39:53My business like customer segment.

39:55Now I can use this as is.

39:58I can also customize it.

40:00So that's interesting.

40:01He clicked on that and it took you straight

40:03into Tableau desktop and it took you into

40:07web edit.

40:09And that animation wasn't authentic.

40:11It kind of just, you know, just added it

40:12and it skipped a few steps.

40:14I think they're deliberately trying to sort

40:15of skip out of those steps because they're

40:18planning this.

40:19This is coming in the future.

40:21It's not sort of worked out yet.

40:22So because this hasn't been announced,

40:25nothing.

40:25So it's not even in the beta anywhere on

40:27Tableau sort of program.

40:29My favorite part of the Einstein discovery

40:30predictions.

40:31I think this is going to be the IT on the

40:32cake.

40:33So what we're doing right now is connecting

40:35to a live predictive model deployed on

40:37Salesforce.

40:38And we're going to bring into the dashboard

40:41real time in context predictions.

40:43And we're going to do this with just a few

40:44clicks.

40:45What I don't like about that demo is that

40:47he just skipped past the reasons he was

40:49clicking what he was clicking.

40:51It was like, you see, you know, amazing.

40:56And okay, I'm sure this should be here, but

40:58nonetheless, it's a bit fast.

41:00Now what I have in relation to my

41:01historical churn rate is predicted churn

41:03likelihood.

41:04This will give me actionable views into my

41:06business and allow I can slice and dice

41:09those however I want with the power of

41:11Tableau.

41:12Now, voila, insights predictions ready for

41:15my team to access.

41:17You've heard maybe that Slack is now part

41:19of the Salesforce family.

41:21Yeah.

41:22And of course I can share in that channel.

41:24Now we're in Slack and check this out.

41:27I see an alert about unfulfilled orders.

41:30I will say I'm currently experiencing a bug

41:33and it's not just me where I can't even get

41:35the Slack app installed.

41:37Sorry, the Tableau app installed in Slack

41:39correctly.

41:40I've filed a ticket with Tableau support

41:41and they've sent me off to Slack support.

41:44So now I'm waiting for Slack support and I

41:45bet you Slack support is going to say go

41:47over to Tableau support.

41:49So I like that they're showcasing this

41:51stuff, but right now I'm on Tableau online.

41:54I'm trying to set this up and it doesn't

41:55work.

41:56So when I make a video about it, I will

41:58show the detail of that.

42:00So, you know, at the point where there's

42:02actually something to see rather than like

42:04a failed install.

42:05I'll show you that sort of whole process.

42:07But nonetheless, I'm always sort of, you

42:10know, resonant when a company says, hey,

42:12look, this is live now.

42:13And, you know, here I am actually trying to

42:15do it and it doesn't work as advertised.

42:17It's some sort of a broken integration.

42:19So let's hope that gets solved quickly.

42:22If you've managed to get Slack working in

42:24your Tableau online environment or Tableau

42:26server environment, let me know.

42:28But if not, this is problematic.

42:30I want to understand this better.

42:31So I'm going to use explain data to show

42:33what's driving that spike.

42:35It looks like something to do with fitness

42:36bars.

42:37Okay.

42:38Now I've got further questions.

42:39So this is funny because I started this

42:41session thinking this was about Einstein

42:43analytics.

42:44And now it's like the greatest hits of

42:46Tableau.

42:47Explain data, Tableau web authoring, the

42:51gallery that we've just talked about,

42:53Einstein being embedded inside a Tableau.

42:56I'm going to use ask data to dive deeper

42:58into that issue right here.

43:00So I'm asking what campaigns are currently

43:01running for fitness bars.

43:03Boom, I get answers and I'm going to take

43:05this suggestion.

43:07Okay.

43:08That is pretty cool.

43:10That is new and that is pretty cool.

43:12In a Slack conversation, he's actually just

43:16sent a question back to, I assume, Tableau.

43:21And ask data has actually somehow responded

43:25with a chart?

43:27That is new.

43:29And it's okay, that just blew my mind.

43:33That is pretty cool.

43:36Conversational analytics in Slack with the

43:39power of Tableau.

43:40I would love to see how resilient that is

43:42to a whole host of questions and datasets.

43:45But nonetheless, I assume you have to treat

43:47the data in a specific way.

43:49Have Einstein analytics do some sort of

43:51questioning and so on.

43:53The question asks, what campaigns are

43:55currently running for fitness bars?

43:57And there's a score.

44:01So I do think it's using Einstein analytics

44:03.

44:03I'm sure there are certain things that have

44:04been set up.

44:05But still, very cool.

44:07Look at that.

44:09There's context, there's a chart.

44:11It's not bad, I don't think.

44:13I think it's pretty good.

44:14By adding end date.

44:16Now you'll see if you look at this really

44:17carefully.

44:18Wow.

44:19The full sports campaign ends on October 1

44:20st.

44:21This is important information.

44:23Something I want to share with my team

44:25because it's actionable.

44:26They're going to be able to work with this

44:29and potentially adjust our future campaigns

44:31to avoid stretching our marketing

44:33facilities.

44:34So there you have it.

44:35In just a few minutes, we brought together

44:37the full power of Salesforce to complete my

44:40analysis.

44:41We leveraged the Salesforce CDP, Tableau

44:44dashboard starters, predictions from

44:47Einstein discovery, and a collaboration and

44:49insights in Slack.

44:51I'm going to hand it back to you, Avni.

44:53Okay, what I will say is that transition

44:56was a bit disingenuous.

44:58I would love to see anyone, anyone at Table

45:01au move through all of those things as

45:03quickly as he did.

45:05And then say they did it in a few minutes.

45:07I think it's fair to say that you could do

45:09that in maybe 10 to 15 minutes, but not in

45:13a few minutes.

45:15I think that is a bit of a stretch.

45:17If I'm wrong though, I'd love to be proven

45:19wrong on this.

45:20If anyone can move through, where did we

45:22even start?

45:24I've even forgotten.

45:25Salesforce CDP, it was that dashboard.

45:28He wanted to add something, clicked on it,

45:31he brought it in.

45:32He wanted some more data.

45:34A new campaign came in, he went off the

45:35dashboard starters, plugged it in, set it

45:38up, wanted to add something from Einstein

45:40analytics, dragged it in, set it up.

45:42Go there, share it with his team on Slack.

45:45People ask questions on Slack, come back,

45:47ask some more questions.

45:49Ask data comes back with a response, adds

45:51another attribute to ask data, it comes

45:53back with a follow-up response.

45:55That in a few minutes, I think is a bit of

45:57a stretch.

45:59And the person doing that, I don't think

46:00would be the same person.

46:02For one person to go through that whole

46:04entire flow, that to me would be something

46:06like a Tableau creator,

46:07someone who's very comfortable going

46:09between Salesforce, Tableau and Slack.

46:12And that kind of user is actually quite

46:13rare.

46:14So I'm not trying to be unfair, but I'm

46:16just critiquing that workflow and thinking

46:18that is a good bit of marketing,

46:21but that flow sells a world and a vision

46:23that I don't think is realistic today yet.

46:27Thanks, Phil. That was an awesome demo.

46:38One of the things that Phil touched on in

46:40his demo is called ask data.

46:42Ask data is an augmented analytics feature

46:44which allows users to discover answers

46:46faster with AI.

46:48With ask data, a business user can ask a

46:50question in natural language.

46:52So this is such a mind mess, God.

46:55So ask data is a Tableau feature and it

46:57looks like here what's happened is they've

46:59brought it to Salesforce.

47:01So they've literally lifted it and they've

47:03started putting inside of Salesforce and it

47:05's working in the Salesforce context.

47:08Very same way we see it working inside a

47:10Tableau.

47:11So this is sort of what you expect.

47:14Salesforce features come into Tableau,

47:16Tableau features go into Salesforce.

47:18It's not quite that third tier integration

47:21where the two minds come together and make

47:23something completely new that you would

47:24never have got before.

47:25Maybe that's what's coming next. So let's

47:27see more.

47:28Such as what are my sales going to be next

47:29quarter?

47:30I get an in-context answer that allows them

47:32to dig deeper.

47:34The best part about it is that this

47:36experience is available in Tableau, Sales

47:38force and we're bringing it to Slack next.

47:41By bringing intelligent insights to your

47:43users, you're helping them get more out of

47:45their data, become more data driven and

47:47ultimately make more confident business

47:50decisions.

47:51But all of that is an example of how we've

47:53brought data science to business users.

47:56We've also made advancements for our more

47:57technical audience.

47:59Introducing multi-class classification.

48:02For all of you out there building models

48:04with Einstein Discovery, Einstein just got

48:06a little bit smarter.

48:08With multi-class classification, you can

48:10now classify a record in up to 10 buckets,

48:13up from the two that were previously

48:15supported.

48:16This means that your predictions can be

48:18more complex.

48:19You can solve for more use cases, all while

48:22maintaining full model explainability

48:24through clicks, not code.

48:26Now that we've seen the power of

48:27intelligent insights...

48:29I mean, we blew right that past right that,

48:32but the key thing that was running in my

48:34mind is how data literate do you have to be

48:37to be doing things at that level.

48:39If I just go back, let's just listen to

48:40that again.

48:41Up from the two that were previously

48:43supported.

48:44This means that your predictions can be

48:46more complex.

48:47You can solve for more use cases, all while

48:49maintaining full model explainability

48:51through clicks, not code.

48:53Yeah, that's the thing.

48:54Using models, data models, right, or

48:56predictive models, sorry, and then you're

49:00classifying things into groupings.

49:02And you're doing it through clicks, not

49:03code.

49:04Okay, fine.

49:06But what I always have to argue is, look,

49:07who exactly is doing this?

49:09Is this like a standard business user?

49:12In my experience, data literacy levels, the

49:16person who's doing this has to have a very

49:18adept level of understanding of that data.

49:22And data literacy to be able to sort of

49:24navigate this kind of tooling and be

49:26comfortable.

49:28And this wasn't the data science level, the

49:30data science level was next.

49:32This is sort of the middle step between,

49:34you know, I am a basic user asking simple

49:36questions and being the business user who

49:38knows their stuff and knows the answers.

49:41Maybe I'm not putting enough faith in the

49:43business user in this sense, but I think,

49:45you know, model explainability.

49:48And I think it's a bit of a stretch. I'm

49:50not trying to be a skeptic. Maybe I'm wrong

49:52. If I'm wrong, let me know in the comments.

49:54Let me know.

49:55Now that we've seen the power of

49:56intelligent insights for every single

49:58person in your business, I'm going to pass

50:00it over to Aline, who's going to walk you

50:02through the final step of building a data

50:04culture.

50:05Over to you, Aline.

50:11Thanks, Agni.

50:13So we've seen some amazing content on how

50:15to unleash the power of your data and

50:18develop a data culture.

50:20But discovering intelligent insights fast

50:23is not where this stops.

50:25Today, I'm excited to talk about how you

50:27can leverage those insights to collaborate

50:29with your team and further develop a data

50:32culture with the newest member of our Sales

50:34force family, Slack.

50:37Our product management team has been hard

50:39at work to develop brand new features so

50:42you can take powerful insights from Tableau

50:44and share them inside of Slack.

50:47Imagine you're a sales rep and you live and

50:49breathe in Slack, collaborating on deals.

50:53You've got a question about your data. You

50:56do not need to exit Slack and jump into a

50:58dashboard because now we've made it

51:00possible with AskData in Slack to ask

51:03questions about your data without ever

51:06leaving the flow of work.

51:08So what if I'm inside of Tableau and I

51:10discover an amazing insight?

51:13So it's interesting here because they're

51:17saying these are coming in spring of 2022.

51:23That is April or May next year.

51:23Well, GA spring 22, that's even further.

51:30Tableau notification Slack is already

51:32available. I don't know what GA means, but

51:34I don't know what GA means.

51:36If you know what GA means, let me know. But

51:38spring 22 is next year and coming 22, that

51:41could be any time next year.

51:43So they're not even given a season and I'm

51:44going to assume it's later than spring 22.

51:47So that's really interesting.

51:49So everything we saw before with AskData in

51:51Slack wasn't actually real because you can

51:53see here that it's coming next year.

51:56So that must have been some sort of product

51:59sort of, you know, walkthrough.

52:02They've sort of skipped through screenshots

52:04as if the feature is working because that's

52:05where they're heading with that.

52:07Hence the forward looking statements that

52:08come at the very beginning, you know,

52:11showing you stuff that's coming, but isn't

52:13necessarily confirmed or baked in.

52:15That I want to share with my team. Do I

52:17need to guide my team to where I found that

52:20insight in Tableau?

52:22No, because now we made it possible to

52:25share dashboards and recommendations from

52:28Tableau inside of Slack.

52:31And with Einstein Discovery in Slack, you

52:34're able to easily and simply see insights,

52:37recommendations and predictions from

52:40Einstein Discovery.

52:42One of the challenges with doing this

52:44outdoors is obviously nature is super windy

52:46.

52:47I have to say that wind, whatever it is on

52:50the lavalier mic, is doing nothing.

52:53I don't know, it must have been the

52:55cheapest windmuff ever.

52:57I've got a small one on a lavalier mic and

52:59honestly, if I stood outside in like a

53:02freaking blizzard, you would still not be

53:05able to hear the wind.

53:06So you can get better live mics, sort of

53:09protectors.

53:11It might be that she's standing literally

53:14facing the wind and her body is sort of

53:17acting like a wind sort of wall.

53:20So the air is sort of going right past the

53:21lavalier in between the lavalier and sort

53:23of where she's got it clipped so you're

53:25hearing it more than you should.

53:27But typically again, lavalier placement, if

53:29you put them in the right place, generally

53:31shouldn't have that much wind sort of

53:33coming through.

53:34Especially if you've actually got a sort of

53:35wind cover on there.

53:37That sounds more like a pop filter rather

53:39than a windmuff.

53:40In fact, let me show you what that should.

53:42I don't know why I'm going on the tangent,

53:44but I love my tech.

53:45So we're going to go on the tangent here.

53:47If I grab this, this, this is a proper wind

53:54muff for a lav mic.

53:57Let's see if I can put that in front of the

53:58camera and get it to focus.

54:00See that?

54:01So the reason it's nice and fluffy is

54:02because that's actually what stops the wind

54:04.

54:05So what it looks like they've done is they

54:06've just put like a pop filter, but it's

54:08doing nothing to block the air that's

54:10actually blowing through that.

54:13So yeah, no pro tips on lavalier mic

54:15placement.

54:17I don't know why I went on that tangent.

54:19It's just annoying me.

54:20So I felt like I had to drop some mic on my

54:22audio equipment.

54:24I don't know why.

54:25Let's carry on.

54:26So we've talked about business science and

54:29we've talked about Slack first analytics.

54:32Let's see these come together in a demo.

54:34I'm going to pass it over to David Lowe,

54:36senior product marketing manager, is going

54:38to show us all of this in action.

54:40David, take it away.

54:42Thanks, Celine.

54:45Hey, everyone, I'm David, and I'm so

54:47excited to be here with you all today for

54:49the purposes of this demo.

54:51I'm not going to be David, the product

54:52marketer.

54:53I'm going to be David, the sales manager,

54:55who works with Phil that you met in the

54:56last demo.

54:57Now, as a sales manager, I lead a team of

54:59sellers, and it's my job to make sure that

55:01they have everything they need in order to

55:03crush their quota every single quarter.

55:06So I need to be on top of my data.

55:08I need to be able to access and share

55:10actionable insights with my entire team.

55:13Fortunately, Einstein can help.

55:16Einstein's discovery for reports looks

55:19across all of my past data.

55:21It's looking to see what the key drivers

55:23are that have affected my team's ability to

55:26win deals in the past.

55:28That's throwing him off because that's not

55:30his slide.

55:31You can see there's a brief moment there

55:33where he was like, that's not my slide.

55:36And it says, "Tablet developer portal and

55:38dashboard extensions API."

55:40So let's see how he kind of rescues this

55:41because you can see here, I've stopped on

55:43the exact frame where he's like, what the

55:45hell is that?

55:47Let's see.

55:51And soon you'll see the demo on screen.

55:56I called it right there.

55:57I definitely have the wrong thing.

56:00Poor guy.

56:01That's not his fault because he hasn't got

56:02one of these clickers.

56:04So it's not him.

56:05They've obviously given him a cue point and

56:06they've gone and gone to the wrong slide or

56:08the wrong demo.

56:09They're supposed to sort of go to specific

56:11points when they say something and they've

56:14gone to the wrong place.

56:17So this is like the worst.

56:21Oh, my word.

56:22And this is not this guy's fault whatsoever

56:24.

56:25Like when this happens to you, when you're

56:27not in control of your own slides and this

56:29happens to you and you had a talking point

56:32that relied on talking about what's on

56:33screen.

56:34And then it doesn't turn up.

56:36You're probably thinking, should I pause

56:37and wait and get the technical issue solved

56:39?

56:40Oh, wait, this is being recording.

56:42Should I try and fill time for air?

56:43It's super tough.

56:45So I feel for this guy.

56:46In the meantime, I'll tell you more about

56:47Einstein Discovery.

56:49Einstein Discovery is now on the screen.

56:52Einstein Discovery.

56:54So well filled.

56:56I love that they got it up right as he was

56:57about to say something else.

56:59It allows me to, with a single click, look

57:02across all of my past.

57:04He's back on track, which is great.

57:06It's looking at my historical data and

57:08going through all the possible combinations

57:11and permutations to understand what the

57:13factors were that helped my team close

57:14deals in the past.

57:16And it's fast.

57:18Right away, Einstein surfaces insights for

57:20me.

57:21Here we can take a look at route to market.

57:23We can see which route to market has most

57:25significantly impacted my team's ability to

57:28close deals.

57:29And then I can have my team focus on that.

57:32But that's not all.

57:33I can take it a step further.

57:35I can use data prep recipe to further

57:37enrich my sales data with no code ML

57:40transforms.

57:42This is interesting.

57:44It's very feels like the DNA of tablet prep

57:46being brought into Salesforce.

57:48So you can kind of start to see why Sales

57:50force acquired Tableau's.

57:53It's a very sort of interesting sort of

57:54thing to see.

57:55Predicting missing values.

57:56Clustering.

57:57Let's take a closer look at clustering.

57:59So what clustering does is it looks across

58:01my opportunities and it starts to group

58:03like accounts.

58:05It's AI powered segmentation that's surf

58:07acing hidden insights into buying patterns

58:09that then inform my white space analysis.

58:12This white space analysis helps my team do

58:15stronger targeting.

58:17More effective targeting.

58:18And within my white space analysis

58:20dashboard, I can drill down to the

58:21individual account level.

58:23Let's take a look at 24/7 convenience

58:25stores.

58:26Based on my white space analysis, I can see

58:28that the rep for this account should

58:29suggest selling energy drinks.

58:31Because other customers within that same

58:32cluster have been successful selling that.

58:35Now this is actionable feedback.

58:38And I need to get it out to my team.

58:40That's where Slack comes in play.

58:42My team works and collaborates in Slack

58:44every single day.

58:45Oop, Tab by CRM in the app.

58:47It's really easy to access dashboards just

58:48like this one and then share it with your

58:50entire team with just a click.

58:52But that's not all.

58:54I can also access Einstein Discovery

58:55directly within Slack.

58:57It's as easy as opening this report,

58:59clicking on run predictions, and getting a

59:01likelihood to close for all of these open

59:04deals.

59:05Not only that, but I get AI powered

59:06recommendations on how to improve that

59:08likelihood as well.

59:10Just a couple more clicks and I've shared

59:12that with my entire team.

59:14Now with all of this AI powered guidance,

59:16my entire team can sell more quickly.

59:19So they need a smarter and faster way to

59:21quote as well.

59:22Fortunately, Einstein is built directly

59:24into my quoting process.

59:26Here you see Einstein suggesting a discount

59:28between 45 and 46 percent.

59:30Along with a prediction on the likelihood

59:32that my customer will accept.

59:34So when my rep submits this quote,

59:36automation makes it so that this quote,

59:39which meets certain criteria, is

59:40automatically accepted.

59:42My team is so much more efficient because

59:43they don't have to wait for me to approve

59:45it.

59:46Now all of this AI powered guidance is

59:48helpful for us anywhere, even when we're on

59:50site with our customers.

59:52Just last week, we were at a customer's

59:54warehouse.

59:55And right from the warehouse floor, I could

59:56take out my phone, scan a barcode with the

59:58Tableau CRM app, and immediately get order

60:01insights, sales data on products.

60:04Now this is insights right where we work

60:06and it really increases our customers'

60:08confidence.

60:09So whether you're working from home, you're

60:10working from the office, or you're working

60:12directly with your customer.

60:14I just want to pause there and go back a

60:15couple of steps.

60:17This to me is really cool. I'm actually

60:19super passionate about this exact field.

60:22What's going on here is you're holding up

60:23an iPad as you can see, and it's

60:25recognizing the QR code and pulling out the

60:28facts.

60:29And it's sort of like augmented reality and

60:31it's sort of superimposing this.

60:34This is actually what I've always imagined

60:36augmented reality to be doing in the real

60:38world.

60:39Like showing analytics and data and

60:41information to people at the point that it

60:43's used.

60:44Imagine a retail floor, imagine being able

60:46to scan a QR code and see the sales

60:48performance for all the items on that

60:50particular shelf or on that particular line

60:52.

60:53It's exactly what's going on here. So I

60:54think this is super smart.

60:56This to me is a version of AR that I think

60:58will get sort of the most proliferated use

61:00out in the business.

61:02Maybe using your phone, moving your tablet,

61:04if we have smart glasses in the future,

61:06those will just have that embedded in.

61:08So maybe I'm a little bit crazy, but I've

61:10always thought this was something that was

61:12going to happen.

61:13It's so good to see it here inside of the

61:16demo.

61:17Now this is Insights right where we work,

61:19and it really increases our customers'

61:21confidence.

61:22So whether you're working from home, you're

61:24working from the office, or you're working

61:25directly with your customers,

61:27Tableau's AI capabilities give you the

61:28insights and the automation that you need

61:30in order to sell more effectively.

61:32Cool. Back to you, Alim.

61:35You rescued that pretty well, given that

61:37Railroaded him halfway through that. That

61:39was pretty good.

61:40That was an amazing demo.

61:42So we've talked about how to better

61:44collaborate around your data with people at

61:47your company, but how do you expand your

61:49network outside?

61:51That's a bit random. I mean, whoever's

61:53doing the presentation cues here is just

61:55off point.

61:56That came up too early. I gave away her

61:58point. No reason to listen to her.

62:01That's where the Tableau community comes in

62:02.

62:03Our Tableau community, #OurDataFam, has

62:06over one million members around the globe

62:09in user groups, online, and when it's safe,

62:12in person.

62:13Now the members of our community don't just

62:15engage in these user groups.

62:17They share their knowledge with the world

62:19on Tableau Public.

62:21Tableau Public today has over 750,000

62:25authors, 4.5 million visits, and 2 billion

62:30views.

62:31Tableau Public is our free data platform

62:33where any one of you can create and share

62:36visualizations.

62:38This is great. I love this. I love this. I

62:40love this.

62:40Because it's very much Tableau, well Slack

62:44as well, basically saying,

62:46"Hey, we already have the community of

62:48people to build stuff. Go find them.

62:51This is how active they are. This is how

62:52much they've done."

62:54So I love this. This is very much Tableau,

62:56Slack, Salesforce, talking to the Sales

62:59force community and telling them,

63:01"Go find these people who already know how

63:03to build stuff. They can build it for you."

63:05That's kind of what she's saying.

63:07Think of it as the YouTube of data.

63:11I've got one more exciting announcement for

63:12you all.

63:13We are announcing our new developer portal.

63:16There you go.

63:17This developer portal is the one-stop shop,

63:19and it allows you to create and build on

63:21our developer platform with its very own

63:24risk-free developer sandbox.

63:26This means any one of you can try new

63:28things and create amazing data experiences.

63:32So now I'm going to pass it back to Mark

63:33with some important action items.

63:36Mark, take it away.

63:38That's pretty cool.

63:39Really interesting place to put the

63:41dashboard developer portal.

63:43I think it's a very interesting place.

63:46I wouldn't have said this was a developer

63:48audience.

63:49Why put that there?

63:51It doesn't quite connect for me, but yeah.

63:55That's very strange, right?

63:57Awesome. Thanks, Aileen. That was great.

64:00So today, we've seen three steps to unle

64:02ashing your data and building a data culture

64:04.

64:05First was speed with fast time to value

64:07with connectors and out-of-the-box

64:09templates.

64:10Next was intelligence, how you can infuse

64:11intelligence so everyone across your

64:13organization can take advantage of AI.

64:16And the last was how to collaborate with

64:18coworkers through Slack and across the

64:20whole Tableau community.

64:22So I want to leave you with three action

64:23items today to get started on your journey

64:26with Tableau.

64:27First is join our data fam.

64:29Learn, ask questions, and get inspired by

64:31data people around the world.

64:34Second is to check out our data channel on

64:36Salesforce Plus for more great analytics

64:39content.

64:40And third, check out salesforce.com/analy

64:42tics to learn more about our products, watch

64:45a demo, join a trial, and more.

64:47Thank you so much for your time today, and

64:49I look forward to seeing you again soon in

64:51person or virtually.

64:53Very cool.

64:55I love that call out to Salesforce.

64:57Come find our community of people that are

64:59already there, right?

65:01You're new, come find them, it's already

65:02active, and I think that's the right way of

65:04doing it.

65:05Why try and split the community? Why try

65:07and merge them?

65:08Instead, just bring the Salesforce

65:10community to Tableau users and vice versa.

65:14Okay, that's pretty much it.

65:21There's a sort of a vision for what Dream

65:23force is, if you can make it, but there we

65:26go, pretty much it.

65:29So there was one last point I just wanted

65:32to make, which was actually about his sort

65:37of image here.

65:38Build a data culture, speed, intelligence,

65:40collaboration.

65:41At the very beginning, he did say that it

65:43was the tool was a small part of that.

65:46There's the people side, and then there's

65:47the tools.

65:48And he very much talked about Tableau being

65:50the tool.

65:51I think Tableau do acknowledges there's

65:52something called the Tableau blueprint.

65:55If I just bring this up, and the Tableau

65:57blueprint here is very much Tableau

65:59acknowledging that this is what you have to

66:02do to get the people side of it working.

66:05And they have it broken down into these

66:07sort of different steps, agility,

66:09proficiency, community.

66:11These are the same things we almost heard

66:13speed, you know, what is it?

66:15What are they using here?

66:16Speed, intelligence, collaboration, it

66:18could almost sort of replace this agility,

66:21proficiency, community.

66:23These are all basically the same words,

66:24right?

66:25And they have this lovely thing of threes,

66:27repetition, repetition, repetition, it

66:29works.

66:30And so this makes a lot of sense.

66:32So if you've ever thought about how does

66:33Tableau think of the people side of this?

66:35Well, this is not something you get with

66:37the product.

66:38I think it's really important to understand

66:40the data culture is sort of an amalgamation

66:43of the people who work in your organization

66:45, the shared values, and how it all comes

66:47together, and how it's developed over time.

66:50There's a sort of some core components of

66:52culture and Tableau acknowledges, and you

66:54don't get a data culture just because you

66:56've purchased Tableau.

66:58It's a really important sort of point to

66:59drum home.

67:00And Tableau recognizes, and there's

67:01something called the Tableau blueprint, the

67:04Tableau blueprint kind of guides you

67:05through how to build on these different

67:07things.

67:08And it's actually a properly sort of well

67:10thought through guide on how to do this.

67:13It's very, very thorough.

67:15And it kind of starts right from the top.

67:17So what your executive team have to do,

67:19where your strategy has to go from, and you

67:22can kind of go into this into lots of depth

67:24and read more about it.

67:26So if I go into the just general overview,

67:28you'll see you get this diagram.

67:30And it's again broken down into these core

67:32components.

67:33And if you look over here on the left hand

67:34side, you've got a lot of things there that

67:36can sort of help you out.

67:38So I just wanted to highlight that it is

67:39there.

67:40It's almost like a product in itself.

67:42It has its own help support document.

67:44But on the people side of the thing, Table

67:46au doesn't leave you hanging.

67:48So if you've ever wondered how to go and do

67:50that people side of the thing, then again,

67:52there's a great guide here that you can go

67:53to and you can find out more about.

67:55I'm surprised they didn't call that out.

67:57I didn't. I'm surprised.

67:58Like, you know, Mark's here talking about

67:59the data culture and he spent a lot of time

68:01on the tools.

68:02But he could have just very simply called

68:03out that, hey, we have something called a

68:05Tableau blueprint, which maps out what we

68:07believe is the best way to go about doing

68:09this.

68:10And that would have been a simple call out

68:11and I think would really help a lot of

68:13Salesforce users who are having to build a

68:15data culture and sort of bring data to the

68:17organization.

68:19So that's sort of this the only point I

68:20made.

68:21So, yeah, that's pretty much it.

68:23I really enjoy that. I found it like a

68:25really interesting talk.

68:27I'm going to check out some of the other

68:28videos in the data channel as well.

68:30I think it's important to do that.

68:31This was very much just one piece.

68:33And although it does talk about lots of

68:34different things, I was pleasantly

68:36surprised to see how much Tableau has been

68:38integrated into Salesforce.

68:40There's a few surprises there.

68:42There's a lot of Tableau capabilities we're

68:45used to seeing as data and explain data

68:47being used almost very liberally inside of

68:50Slack and inside of Salesforce as well.

68:53So this is a great opportunity for a Table

68:55au user because suddenly your knowledge now

68:57applies itself to other platforms.

69:00And you can maybe expand your community and

69:02expand your network and even go work in

69:04some of these new places as well.

69:06So that's a really sort of great

69:07opportunity.

69:08But that's it for me.

69:10What are your thoughts? Let me know in the

69:11comments below.

69:12I'd love to know what you thought.

69:13What did you think of this format? Me sort

69:15of just talking through a particular video.

69:17It's a bit weird because the actual session

69:19is 26 minutes and this video is definitely

69:21not 26 minutes.

69:23So it does take a bit longer, but it's just

69:24an interesting thing I might do for future

69:27sessions.

69:28Maybe chop them into parts to sort of make

69:30them a little bit more digestible.

69:32We have the Tableau conference coming up

69:33and hoping to do something with Ravi again.

69:36But if we don't get a chance to do that,

69:37then we'll definitely do something

69:39ourselves.

69:40Maybe even livestream at the event.

69:43So yeah, check that out.

69:44Thanks for watching.

69:45If you enjoy this, you know what to do.

69:46If not, let me know in the comments below

69:48and I'll catch you in the next one as I

69:49knock my mic as I try and sign off for

69:51today.

69:52Take it easy.

69:53Bye.

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