Why Data Cleaning Still Sucks
Data cleaning is nobody’s favorite part of analytics. For the typical business user, you’ve got messy spreadsheets, inconsistent formats, duplicate records, and values that make no sense. And if you’re not a SQL expert, you’re usually stuck doing everything manually in Excel.
Tableau Prep changes that. It’s a visual data preparation tool that lets you clean, shape, and combine data without writing a single line of code. If you can drag and drop, you can use Tableau Prep.
Here’s what you need to know to get started.
What Is Tableau Prep, Anyway?
Tableau Prep is Tableau’s answer to the data preparation problem. It sits between your raw data sources and Tableau Desktop, giving you a visual way to:
- Connect to multiple data sources (Excel, databases, cloud apps)
- Clean messy data (fix typos, handle nulls, standardize formats)
- Transform data (split columns, pivot tables, create calculated fields)
- Combine datasets (joins, unions, aggregations)
- Output clean data ready for analysis
Think of it as ETL (Extract, Transform, Load) for people who don’t know what ETL is.
Getting Your First Flow Set Up
A “flow” in Tableau Prep is basically your data pipeline. Here’s how to build one:
Step 1: Connect Your Data
Open Tableau Prep and click “Connect to Data.” You’ll see options for Excel, CSV, databases (SQL Server, PostgreSQL, etc.), and cloud sources like Google Sheets or Salesforce.
For this example, let’s say you’re working with a messy sales CSV file. Connect to it, and Tableau Prep will show you a preview of your data.
Step 2: Add a Clean Step
Drag your data source onto the flow pane. This creates an “Input” step. Now click the plus icon and add a “Clean Step.”
This is where the magic happens. The Clean Step gives you a profile view of every column in your dataset:
- See the distribution of values
- Identify nulls and outliers
- Spot data quality issues at a glance
For example, if your “Product Category” column has values like “Electronics,” “electronics,” and “ELECTRONICS,” you’ll see them all listed separately. That’s a problem you can fix.
Step 3: Clean Your Data
Here are the most common cleaning operations you’ll use:
Fix Inconsistent Values: Right-click on similar values (like “Electronics” and “electronics”) and choose “Group Values.” Tableau Prep will standardize them to one value.
Handle Nulls: Click on null values in a column and decide what to do—replace them with a default value, filter them out, or leave them.
Split Columns: If you have a “Full Name” column that you want to split into “First Name” and “Last Name,” right-click the column and choose “Split Values.” Tableau Prep will auto-detect the delimiter (usually a space).
Rename Columns: Double-click any column header to rename it. Use clear, descriptive names.
Change Data Types: Click the data type icon (like “Abc” for text or “#” for numbers) to change how Tableau interprets the column.
Step 4: Add Calculated Fields
Need to create new columns based on existing data? Click “Create Calculated Field” and write a simple formula, just like you would in Tableau Desktop.
For example, if you have “Unit Price” and “Quantity” columns, you can create a “Total Sales” field:
[Unit Price] * [Quantity]
Tableau Prep uses the same calculation syntax as Tableau Desktop, so if you know one, you know the other.
Step 5: Filter Your Data
Add a “Filter” step to remove rows you don’t need. For example, you might filter out:
- Test records
- Incomplete orders
- Data from previous years
- Specific regions or products
Just click “Add Filter,” choose your column, and set your criteria. Easy.
Combining Multiple Data Sources
Most real-world scenarios involve more than one dataset. Tableau Prep makes it simple to combine them.
Joins
If you have two datasets with a common key (like “Customer ID”), you can join them together.
Drag both data sources into your flow, then drag one onto the other. Tableau Prep will automatically suggest join keys based on matching column names. Review the join, adjust if needed, and you’re done.
You’ll see a visual representation of the join (inner, left, right, or full outer) with row counts so you know exactly what’s happening.
Unions
If you have multiple files with the same structure (like monthly sales reports), you can stack them into one dataset with a union.
Drag the first file into your flow, then drag additional files onto it and choose “Union.” Tableau Prep will align the columns automatically. If column names don’t match perfectly, you can manually map them.
Aggregations
Need to summarize your data? Add an “Aggregate” step and choose which fields to group by and which to aggregate (sum, average, count, etc.).
For example, you could aggregate sales data by month and product category to see total revenue per category per month.
Output Your Clean Data
Once your flow is set up, add an “Output” step at the end. You can save your clean data as:
- A Tableau extract (.hyper file) for use in Tableau Desktop
- A CSV file for use in other tools
- A database table (if you have write access)
Click “Run Flow” and Tableau Prep will process everything and generate your output. The first run might take a few seconds, but subsequent runs are faster, especially if you’re working with the same data source.
When to Use Tableau Prep (And When Not To)
Use Tableau Prep when:
- You need repeatable data cleaning workflows
- You’re combining multiple sources for Tableau analysis
- You want a visual, no-code approach
- You need to collaborate with non-technical users
- You’re building automated data pipelines
Don’t use Tableau Prep when:
- You need complex transformations that require custom code
- You’re working with extremely large datasets (billions of rows)
- You need real-time streaming data processing
- You already have a robust ETL tool that works well
Tableau Prep is powerful, but it’s not a replacement for every data engineering tool. It’s best for medium-scale data prep that needs to be visual and accessible.
Conclusion
Tableau Prep takes the pain out of data cleaning for people who don’t want to write code. You get a visual interface, instant feedback, and the ability to build repeatable, automated workflows.
If you’re already using Tableau Desktop for analysis, Tableau Prep is the natural complement. Clean data in Prep, analyze it in Desktop, and stop wasting time on manual data wrangling.