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Tableau Prep Parameters: New in Tableau 2021.4

Parameters finally bring Tableau Prep flows to life, letting you build dynamic, scenario-driven pipelines.

Part ofWhat's new in Tableau 2021.4Tableau Prep Builder tutorial Jan-2020
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  • Parameters in Tableau Prep work anywhere you see the abacus icon, including calculation windows and output steps, and exist throughout the entire flow.
  • To filter with a parameter, create a calculated field that returns a Boolean (e.g. segment = segment parameter), then keep only the values that are true.
  • Editing a parameter opens a modal window so you can view your data while changing values, and you can click back to previous steps to inspect data without undoing work.
  • Output steps let you parameterise both the file name and location, for example appending the segment value to the file name.
  • Enabling 'prompt for value at runtime' makes the flow ask for the parameter each time it runs, even on server, which is ideal for scenario modelling.

Tableau Prep 2021.4 adds parameters, letting you build flows that respond to a value the user sets, whether that's filtering data, changing output file names/locations, or prompting for a value each time the flow runs. This turns static Prep flows into dynamic, scenario-driven pipelines.

Demonstrated on a sample sales flow with a segment field (consumer, corporate, home office). The aim is to let someone running the flow choose which segment to process without editing the flow itself.

The Breakdown
  1. Create a parameter anywhere via the abacus icon 0:35

    Parameters exist throughout the whole flow, not tied to one step. You can create or edit one anywhere you see the abacus icon — in calculation windows or output steps — and give it a default value and a data type.

  2. Pick a good step to apply the parameter 2:01

    Choose the point in your flow where the parameter should take effect, ideally somewhere it can affect all downstream branches, rather than applying it separately in multiple places.

  3. Filter with a Boolean calculation 2:36

    To filter using a parameter, you must first create a calculated field that compares a data field to the parameter (e.g. segment = segment parameter), which returns true/false, then use a filter step to keep only the true rows. This two-step pattern — a tagging calculation followed by a filter — is what actually does the filtering.

  4. Turn a parameter into a value list 3:50

    Editing a parameter opens a modal window so you can inspect your data while changing the value, and you can click back to earlier steps to preview data at that point without undoing anything. You can convert a single value into a list of allowed values (note: existing values don't pre-populate, so you retype them) so users pick from a dropdown instead of typing free text.

  5. Use parameters for scenario modelling 5:29

    Any adjustable value — a filter, a percentage, a threshold — can become a parameter that different users set differently when they run the flow, letting each person generate their own scenario or dataset from the same flow.

  6. Parameterise output file names and locations 6:37

    In an output step, you can use a parameter to build the file name (e.g. appending the segment value) and, separately, the output location. You can also click directly on the output text to change the parameter value from that step.

  7. Prompt for values at runtime 8:17

    Enabling 'prompt for value at runtime' on a parameter makes the flow ask for that value every time it runs, including on server, so each run can process a different scenario without manually editing the flow first.

Worth Knowing
  • When converting a parameter to a value list, the current value doesn't pre-populate — you need to retype it as one of the list entries.
  • There's a minor UI quirk where text spacing in output file names doesn't align exactly with the highlighted parameter insertion point.
  • Output locations can only use parameters, not fields from the data itself — Tim notes this is something he'd like added, comparing it to Alteryx's ability to use a column for file paths.
  • This is conceptually similar to Alteryx 'constants' — a value you set once and reference throughout a flow.
Use It When

Reach for this when you want one Prep flow to serve multiple people or scenarios — for example letting different users filter to their own segment, apply their own percentages, or generate personalised output files — without duplicating the flow or editing it by hand each time.

How this Rollup was made provenance & method

A Rollup is drafted by AI from the video's transcript, then reviewed and edited by Tim. Everything used to produce this one is listed below — the model, the exact prompt, and the source video — so the process is transparent and reproducible.

Transcription
On-device — NVIDIA Parakeet v3 for recent videos, OpenAI Whisper large-v3 for earlier ones. The transcript never leaves the machine or gets published.
Drafting
Claude Sonnet 5 in the cloud, from that transcript.
Prompt
The exact Rollup prompt (v2) — the full system prompt, unedited.
Source video
Watch on YouTube
Drafted
5 July 2026 at 09:38
Reviewed & edited
5 July 2026 at 09:41 · by Tim Ngwena

Model + prompt + video is everything you'd need to recreate a Rollup like this yourself. The one thing we don't share is the transcript.

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