What is Split in Tableau?

Ever get a single column of data that crams too much information together? Think of a "Full Name" field that you wish was separate "First Name" and "Last Name" columns, or a product SKU like ‘TSHIRT-BLUE-LARGE’ that you need to break down into category, color, and size. This kind of data wrangling is a constant headache, but Tableau has a simple, built-in solution. This article will show you exactly how to use Tableau's Split and Custom Split features to easily clean and organize your data for better analysis.

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What is Split in Tableau?

In simple terms, Tableau's Split function is a tool that breaks up text data (known as strings) from one column into multiple new columns. Imagine you have a piece of yarn with several knots in it. The Split function is like a pair of scissors that cuts the yarn at each knot, giving you several smaller pieces.

Those “knots” in your data are called delimiters. A delimiter is simply a character that separates different pieces of information. It could be a space, a comma, a hyphen, a period, or any other consistent character. Tableau searches for these delimiters to understand where it should make the "cuts."

Tableau offers two primary ways to perform a split:

• Split: This is the automatic, one-click option. Tableau analyzes your data, guesses the most common delimiter, and splits the column accordingly. It’s fast, easy, and works great for simple, consistent data.
• Custom Split: This gives you more control. You tell Tableau exactly which delimiter to use, how many new columns to create, and which parts of the original string you want to keep. This is your go-to when the automatic split doesn't get it quite right.

When to Use the Split Function

Splitting columns is one of the most common data preparation tasks. You'll find yourself reaching for it in many situations, especially if you work in marketing, sales, or e-commerce. Here are a few relatable examples:

• Separating Names: The most classic use case. Splitting a single Full Name column into First Name, Middle Name, and Last Name columns to personalize email campaigns or analyze customer data.
• Deconstructing Product Info: Splitting a Product SKU like SHOES-LEATHER-BROWN-11 into separate columns for Category, Material, Color, and Size. This allows you to analyze sales based on specific product attributes.
• Breaking Down Geographic Data: You might get a field like Boston, MA, 02110. Splitting this by the comma would give you separate dimensions for City, State, and Zip Code, making it easy to create maps and regional reports.
• Parsing User Info: You could split an email address like info@companyname.com using the "@" symbol to isolate the User and Domain. This can be useful for grouping customers by their organization.
• Extracting Order IDs: Sometimes order and customer information is combined, like ORD-98765-CUST-3456. You can use the Split function to pull out just the order number or the customer ID.

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How to Use the Automatic Split in Tableau

Let's walk through an example. Imagine we have campaign data with a field called "Campaign Source / Medium" that looks like google / cpc, and we want to analyze the source and medium separately.

The automatic Split function is perfect for this.

Step 1: Locate Your Field in the Data Pane On the left side of your Tableau worksheet, find the "Data" pane. Scroll through your list of dimensions and find the field you want to split. In our case, it's Campaign Source / Medium.

Step 2: Right-Click and Choose Split Right-click on the Campaign Source / Medium field. A context menu will appear. Hover over Transform, and then click on Split.

Step 3: Check Your New Fields Instantly, Tableau gets to work. It detects that the forward slash (/) is the common separator in this field. It then creates two new fields in your Data pane:

• Campaign Source / Medium - Split 1
• Campaign Source / Medium - Split 2

That's it! You now have two separate fields. For clarity, it's a good practice to rename these new fields. Just right-click on each one, select Rename, and change them to "Campaign Source" and "Campaign Medium". Now you can drag these new fields into your view to analyze performance by source or medium independently.

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Taking Control with Custom Split

The automatic Split is fantastic for simple tasks, but what happens when things are more complicated? Maybe your data has multiple delimiters, or you only want to pull out a specific piece of information. This is where Custom Split comes in handy.

Let's use an example of a product code: WTR-BOTTLE-SSTL-24OZ. This represents Category-Product-Material-Size.

Suppose we only want to extract the first two parts: Category and Product. The automatic split would give us all four. Custom Split gives us the control to get exactly what we need.

Step 1: Locate and Right-Click Your Field Just like before, find Product Code in your Data pane and right-click on it.

Step 2: Choose Custom Split Go to Transform > Custom Split.... This will open a dialog box where you can define your own rules.

Step 3: Configure Your Split The Custom Split window gives you three options to configure:

• Use the separator: This is where you tell Tableau which character to use as the delimiter. For our product code WTR-BOTTLE-SSTL-24OZ, the delimiter is a hyphen (-).
• Split off: This powerful setting tells Tableau which parts of the string you want to keep.
• Columns: This tells Tableau how many columns to create based on your "Split off" choice.

Since we want the first two parts (WTR and BOTTLE), we'll set it up as follows:

• Use the separator: -
• Split off: First
• Columns: 2

Once you click "OK", Tableau creates Product Code - Split 1 (containing WTR) and Product Code - Split 2 (containing BOTTLE), ignoring the rest. This precision saves you from creating extra, unwanted columns.

Advanced Power: Splitting with a Calculated Field

For the ultimate level of flexibility, you can use the SPLIT() function directly within a Tableau Calculated Field. This method is incredibly powerful because you can nest it within other functions like IF statements or combine it with other calculations.

The syntax for the SPLIT() function looks like this:

SPLIT(string, delimiter, token number)

Let's break down each component:

• string: The text field you want to split. For example, [Product Code].
• delimiter: The character that separates the data, enclosed in quotes. For example, "-".
• token number: The specific part you want to return. This is an integer. 1 gets the first part, 2 gets the second part, 3 the third, and so on. A helpful trick is that you can use a negative number to count from the end! For instance, -1 gets the last part, and -2 gets the second to last.

Using our same product code, WTR-BOTTLE-SSTL-24OZ, let’s say we only want to extract the material (SSTL), which is the third part. Instead of using the UI, we can create a calculated field:

Step 1: Go to Analysis > Create Calculated Field. Step 2: Name your calculation something descriptive, like "Product Material". Step 3: Enter the following formula:

SPLIT([Product Code], "-", 3)

And that's it! This calculation will now appear as a new field that returns only SSTL. This method is cleaner and more efficient if you only need one or two specific pieces from a longer string, as it prevents you from creating a series of temporary Split 1, Split 2, etc. fields in your data pane.

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Common Issues & Tips for Success

While the Split function is straightforward, you can sometimes run into issues with messy data. Here are a few tips to keep in mind:

• Watch for Inconsistent Delimiters: If your delimiter isn't consistent, the split won't work correctly. For example, if some product codes use a hyphen (-) and others use an underscore (_), you'll need to clean the data first, perhaps with a REPLACE() function in a calculated field.
• Beware of Extra Spaces: Leading or trailing spaces can throw off your splits. If you suspect this is an issue, you can clean your field using the TRIM() function before splitting. For example: SPLIT(TRIM([Full Name]), " ", 1). This removes any extra spaces from the beginning or end of the name before the split occurs.
• Mismatched Column Counts: When splitting names, remember that some people have middle names and some do not. An automatic split on "John Fitzgerald Kennedy" will produce three columns, but on "John Doe" it produces two. This may leave null values in the third column, which is usually fine but is something to be aware of during your analysis.
• Check Data Types: Tableau's Split function always creates new string (text) fields. If you split a field like Revenue-USA and get 15000 in a new column, remember that it's still text. If you want to perform math on it, right-click the new field, go to Change Data Type, and select a numeric type like Number (whole).

Final Thoughts

Mastering Tableau's Split function is a fundamental step toward becoming proficient in data preparation. Whether you use the quick automatic Split for simple tasks, the focused Custom Split for more specific needs, or the powerful SPLIT() calculation for ultimate control, breaking apart cluttered data is essential for creating insightful and clean visualizations.

Of course, prepping data with tools like Split is often just the beginning of the manual work required to get performance insights. At Graphed, we’ve put a lot of thought into eliminating that friction. We believe you should spend less time preparing your data sources and more time acting on them. By connecting tools like Google Analytics, Salesforce, and Shopify, we automate much of the complex data wrangling for you, allowing you to ask questions in plain English - like "Compare revenue by campaign from Facebook Ads and Google Ads last month" - and get instant dashboards, without having to manually split, clean, or merge a single column.