How to Use Tableau Prep Flow in Tableau Desktop

Switching between Tableau Prep and Tableau Desktop can feel like you're working with two different tools, but they’re designed to be a powerful duo. Prep handles the messy data cleanup, and Desktop turns that clean data into beautiful, insightful dashboards. This guide will show you precisely how to build a simple workflow in Tableau Prep and connect it to Tableau Desktop, creating a smooth and repeatable analytics process.

Graphed

Your AI Data Analyst to Create Live Dashboards

Connect your data sources and let AI build beautiful, real-time dashboards for you in seconds.

Build Your First Dashboard

What is Tableau Prep and Why Should You Bother?

Think of your analytics process like cooking a gourmet meal. Tableau Desktop is your presentation - the beautifully plated dish served to your guests. Tableau Prep Builder, on the other hand, is your kitchen - it's where you do all the messy, essential prep work like chopping vegetables, measuring ingredients, and cleaning everything up before you start cooking.

While you can do some basic data cleaning directly in Tableau Desktop, it’s not built for heavy-duty tasks. That's where Tableau Prep comes in. It provides an intuitive, visual interface to clean, shape, and combine your data before you ever start building charts.

Key advantages of using Tableau Prep include:

• A Visual Workflow: Instead of writing code or complex formulas, you build a cleaning process by dragging and dropping steps. You can see how each action (like removing columns or filtering rows) impacts your data profile instantly.
• Complex Tasks Made Simple: Pivoting data from wide to long, joining files from different sources, or grouping dozens of messy text variations (e.g., "Cal.", "Cali", "California") into one clean category is straightforward.
• Repeatable and Reusable: The entire process you build is saved as a "Flow" file (a .tfl file). The next time you get a new version of your messy data file, you just run the Flow again to clean it instantly. No more repeating manual steps in Excel every week.

Part 1: Building a Basic Flow in Tableau Prep

Let's walk through a realistic scenario. Imagine you receive a weekly sales report as a CSV file. The data is a bit messy: it has empty columns, inconsistent state abbreviations, and a field that combines the product category and sub-category together. We'll use Tableau Prep to fix it.

AI for Data Analysis

Crash Course

Graphed

Free PDF Guide

AI for Data Analysis Crash Course

Learn how to get AI to do data analysis for you — the best tools, prompts, and workflows to go from raw data to insights without writing a single line of code.

Download Free Guide

Step 1: Connect to Your Data

First things first, open Tableau Prep Builder. In the "Connect" pane on the left, you'll see a list of data sources.

1. Click on "Connect to Data."
2. For our example, we're using a CSV file, so select "Text File."
3. Navigate to your data file (.csv, .xlsx, etc.) and select it. Tableau Prep will immediately show you a preview and profile of your data.

You'll see a "flow" pane at the top. The first icon represents your data source. This is the starting point of your recipe.

Step 2: Add a Cleaning Step

This is where the magic begins. The "Clean Step" is your main tool for tidying up the data.

Click the plus icon (+) next to your input step and select "Clean Step."

This adds a new step to your flow. When you click on it, the bottom panel transforms into a detailed view of your data fields. You'll see a profile of each column, showing data types, value distributions, and more. This immediate feedback helps you spot issues right away.

Step 3: Perform Some Common Cleaning Actions

With our Clean Step selected, let's fix the problems in our data.

Removing Unnecessary Columns

Our sample data might have a column called "Notes" that is entirely empty or irrelevant. In the data pane, find the "Notes" column, click the three-dots menu (...) on the column, and select "Remove." Easy.

Splitting a Merged Column

Let's say we have a column named "Product_Info" that contains values like "Furniture-Chairs" or "Technology-Phones." We want this separated into "Category" and "Sub-Category" columns.

• Click the menu on the "Product_Info" column.
• Choose "Split Values" and then "Automatic Split." Tableau is smart enough to detect the common delimiter (the hyphen) and will automatically create two new columns: "Product_Info - Split 1" and "Product_Info - Split 2."
• Rename them by double-clicking the column headers: change "Product_Info - Split 1" to "Category", and "Product_Info - Split 2" to "Sub-Category." You can then remove the original "Product_Info" column to keep your dataset tidy.

Grouping and Standardizing Values

Our "State" column has inconsistent entries: "NY," "N.Y.," and "New York." We want to standardize them all to "NY."

• Click on the menu for the "State" field.
• Select "Group Values" and choose "Pronunciation" or "Manual Selection."
• With "Manual Selection," select "N.Y." and "New York," then right-click and select "Group." The grouped value will be one of the selected values, then you can edit it to be "NY." Now, all three variations are standardized in a single clean value.

As you perform these actions, notice how the flow pane adds icons for each change within your "Clean Step." Click on them to edit or remove actions, giving you full control over your cleanup process.

Graphed

Your AI Data Analyst to Create Live Dashboards

Connect your data sources and let AI build beautiful, real-time dashboards for you in seconds.

Build Your First Dashboard

Part 2: Connecting the Prep Flow to Tableau Desktop

Okay, your data is now sparkling clean. How do you get it into Tableau Desktop to start building visualizations? This is the most crucial part, and it's simpler than you might think.

You don't connect Tableau Desktop directly to the flow file (.tfl). Instead, you create a clean output file from your flow, and then connect Desktop to that output.

Step 1: Add an Output Step in Tableau Prep

In your flow pane, click the plus icon (+) next to your final cleaning step and select "Output." This adds the final step to your recipe.

Step 2: Configure Your Output

When you click the new Output step, the configuration pane lets you choose what kind of output you want to create.

1. For the "Output type," choose "File." (You can also publish directly to Tableau Server/Online or write a database table, but "File" is most common for individual use).
2. Click the "Browse" button to select where to save your file and what to name it (e.g., Cleaned_Sales_Data).
3. Choose the "Output file format." The best option is Tableau Data Extract (.hyper). A .hyper file is Tableau's proprietary, high-performance data format. It's highly compressed and optimized for fast queries and visualizations inside Tableau Desktop.
4. Under "Write Options," select "Create table" if it's the first time running, or "Replace data" for subsequent runs.

Step 3: Run the Flow

This is it! At the bottom of the Output pane, click the big blue "Run Flow" button.

Tableau Prep will execute all your defined steps—from connecting to raw data, cleaning, splitting, grouping, and finally writing the clean dataset to the .hyper file you specified.

AI for Data Analysis

Crash Course

Graphed

Free PDF Guide

AI for Data Analysis Crash Course

Learn how to get AI to do data analysis for you — the best tools, prompts, and workflows to go from raw data to insights without writing a single line of code.

Download Free Guide

Step 4: Connect from Tableau Desktop

With your .hyper file created, connecting to it is straightforward:

1. Open Tableau Desktop.
2. On the startup screen, under the "Connect" section on the left, find "To a File."
3. Click "More..."
4. Navigate to the folder where you saved your .hyper file (e.g., Cleaned_Sales_Data.hyper), select it, and click "Open."

And Voilà! Your cleaned data loads instantly into Tableau Desktop's Data Source page. The column names are correct, data is standardized, and unwanted columns are gone. You’re now ready to drag and drop fields onto the canvas and build your visualizations without wasting time on data prep.

Best Practices for a Smooth Workflow

To make this process even more efficient, keep these tips in mind:

• Organize your files: Create a logical folder structure—one for "Raw Data," another for "Tableau Prep Flows," and another for "Cleaned Data Outputs (.hyper files)." Keep your projects tidy.
• Automate your flows: If you have access to Tableau Server or Tableau Cloud with the Data Management Add-on, you can use Tableau Prep Conductor to schedule flows to run automatically (e.g., every morning at 6 AM). This keeps your .hyper or published data source fresh without manual clicks.
• Comment your steps: In Tableau Prep, right-click any step to add descriptions. For example, "Grouped state names to standardize abbreviations." This helps when revisiting flows later.

Final Thoughts

Connecting a Tableau Prep flow to Tableau Desktop is a simple yet powerful pattern. By making your data prep reusable, you can consistently turn messy data into analysis-ready datasets. The key is to generate a .hyper file from your flow and use that as your data source in Tableau Desktop.

While mastering Tableau Prep is a valuable skill, this workflow bridges the gap between data cleaning and visualization effortlessly. At Graphed, we streamline this entire process—connecting directly to raw data sources and enabling natural language commands to handle data cleaning and dashboard creation in one seamless platform. Just ask, "Show me this month's revenue by state, and combine 'NY' and 'New York' into one," and we’ll generate your interactive dashboard instantly—no need to juggle multiple programs.