What is a Tableau Flow?

Prepping your data is often the most time-consuming and frustrating part of any analysis project. Before you can build even the simplest chart, you have to find your data, clean it up, merge it with other sources, and get it into a usable format. This is where Tableau Flow comes in. In this tutorial, we'll walk through exactly what a Tableau Flow is, how it works inside Tableau Prep Builder, and why it's such a game-changer for anyone who deals with messy data.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

What is a Tableau Flow?

A Tableau Flow is a visual, step-by-step roadmap of your data preparation process, created within the Tableau Prep Builder application. Think of it as a recipe you create for your data. You start with your raw, messy ingredients (like Excel files, database tables, or CSVs), and each step in the flow is an action you take - like chopping vegetables, mixing ingredients, or baking - to turn them into a finished, analysis-ready meal.

Each action you perform, whether it's filtering rows, combining files, or renaming columns, is represented by a distinct visual block on a canvas. You connect these blocks to create a "flow" that documents the entire journey of your data, from its original state to the clean and polished output you can use in Tableau Desktop or other tools. This visual nature is what makes Flows so powerful, you can see exactly what's happening to your data at every single stage.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

The Core Components of a Tableau Flow

When you open Tableau Prep Builder and start working, you'll build your Flow using a few key building blocks. Understanding what each one does is the first step toward mastering data prep.

1. Input Step

Every Flow starts with an Input step. This is where you connect to your data sources. Tableau Prep can connect to a wide variety of data types, including:

• Flat files like Microsoft Excel spreadsheets and Comma Separated Value (.csv) files.
• Statistical files like SAS and SPSS.
• Tableau Extract files (.hyper).
• Connections to cloud and on-premise databases like SQL Server, PostgreSQL, Oracle, and Google BigQuery.

You simply drag the data source you want to use onto the Flow pane (the main canvas), and it becomes your starting point.

2. Clean Step

The Clean step is where most of the magic happens. This is your primary workbench for tidying up a single data source. When you add a Clean step, Tableau Prep shows you a detailed profile of your data, including a metadata grid, a summary of each column, and histograms showing the distribution of values. This profile pane makes it easy to spot issues at a glance.

Common tasks you'd perform in a Clean step include:

• Filtering Data: Keep or exclude rows based on specific conditions. For example, you might filter a sales dataset to only include transactions from the last year or a certain region.
• Removing Unnecessary Columns: If your dataset has twenty columns but you only need five for your analysis, you can simply remove the rest to reduce clutter.
• Changing Data Types: Tableau is smart about guessing data types, but sometimes it needs help. You might need to change a column that's being read as text into a number or a date field being read as a string into a proper date format.
• Dealing with Null Values: You can choose to filter out rows with null values, fill them with zero, or replace them with an average or fixed value.
• Splitting, Merging, and Renaming Columns: Easily split a "Full Name" column into "First Name" and "Last Name," or rename cryptic column headers (like "cust_id") to something more readable ("Customer ID").

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

3. Transformational Steps (Joins, Unions, Pivots, and Aggregates)

Data rarely lives in a single, perfectly structured file. More often than not, you need to combine, reshape, or summarize it. Tableau Flows have dedicated steps for these more complex transformations.

Joins & Unions

These two steps are fundamental for combining data, but they do different things:

• Joins: Combines datasets by adding new columns based on a shared field. For example, you can join a table of customer information (with columns like Customer ID, Name, City) to a table of sales transactions (with columns like Purchase Date, Product, and Customer ID). The "Customer ID" is the common key that links them.
• Unions: Combines datasets by stacking them and adding rows on top of each other. This only works if the datasets have the same column structure. It's perfect for combining multiple monthly or weekly reports into one single master table.

Pivots

A Pivot step changes the shape of your data by transposing columns to rows (or vice versa). For example, if you have a spreadsheet with a column for the year, another for Product, and then twelve more for Revenue, you'd end up with a very wide table. You could use a Pivot to transform the data into a more manageable format, allowing you to conduct monthly analysis efficiently.

Aggregates

An Aggregate step is used to summarize your data at a higher level of detail. Instead of analyzing hundreds of thousands of individual sales, an aggregate can be added. For instance, rather than examining single individual sales, you might want to view the total sales amount. This process allows you to see the big picture, such as total sales per quarter or average sales price.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

4. The Output Step

The Output step finalizes your Flow. When you click Save, a clean dataset is produced. You define precisely how you want to save this data in the Output window options. After prepping it, the output result becomes your analysis-ready dataset, which can be saved as a .csv, .hyper, or another preferred format. The Flow allows you to either output your file for use in Tableau Desktop or send it to a server or cloud for further analytics.

Benefits of Using Tableau Flow

Key Benefits of Tableau Flow Analytics Workflow

Utilizing Tableau Flow in your analytics workflow offers several advantages:

• Highly Visual and Intuitive: The visual interface simplifies complex data preparation tasks, making it accessible even to those without extensive technical knowledge.
• Repeatable and Automatic Data Preparation: Once you create a Flow, it can be reused, significantly reducing time spent on repetitive data preparation tasks.
• Seamless Integration: Flows integrate seamlessly with Tableau's analytics environment, allowing for quick and easy data visualization and reporting.
• Reduction of Human Error: The structured approach to data preparation reduces the risk of errors, ensuring more reliable results.
• Accessibility for Non-technical Users: Tableau Flow is designed to be user-friendly, meaning individuals without programming skills can effectively prepare and analyze data.

Final Thoughts

Tableau Flow is an advanced yet user-friendly tool within the Tableau ecosystem, providing powerful data preparation capabilities. It simplifies the transformation of complex data sets into ready-to-use formats, offering significant time savings and improved accuracy in data analysis. Users can effortlessly connect multiple data sources, automate workflows, and produce high-quality outputs for dashboards and reports, making it an essential tool for efficient data analysis processes.

We created Graphed to help accelerate your data analysis journey, empowering you with even faster dashboard creation and insights without the complexity of traditional tools. Join us to experience streamlined analytics at your fingertips.