Using Qlik Regex to Organise Messy Comment Fields

Source: Dev.to

Free‑text fields are both a blessing and a curse.
They give users flexibility, but from a reporting point of view they’re often messy, inconsistent, and hard to work with. In this case, a customer had a Comments field where users manually typed information, but inside that text was a specific code they needed for reporting.

The requirement was simple on paper:

Extract a code from a free‑text comments field.

In reality… not so simple.

The Problem

The source field looked something like this:

"Breakdown reported – REF12345 vehicle unavailable"
"Job completed ABC 67890 no further action"
"Awaiting parts – no reference provided"

The rules for the code were consistent:

• 3 uppercase letters
• Optional space
• 5 digits

Examples of valid codes:

• ABC12345
• ABC 12345

The challenge:

• The code could appear anywhere in the text.
• Some rows didn’t contain a code at all.
• We needed a clean output suitable for filtering and analysis.

Why Regular Expressions?

You could try to solve this with string functions like Mid(), Left(), or Index(), but that approach quickly falls apart when:

• The position of the code varies.
• The spacing isn’t consistent.
• The text contains lots of noise.

Regular expressions (regex) are designed for exactly this kind of pattern matching.

The Solution

This is the expression I used:

Coalesce(
    Replace(
        ExtractRegEx(
            [Comments],
            '[A-Z]{3}\s?\d{5}',
            1
        ),
        ' ',
        ''
    ),
    'NOT FOUND'
)

Step 1: Extract the Code with ExtractRegEx

ExtractRegEx(
    [Comments],
    '[A-Z]{3}\s?\d{5}',
    1
)

Regex pattern

• [A-Z]{3} → exactly 3 uppercase letters
• \s? → optional space
• \d{5} → exactly 5 digits

This tells Qlik: “Find me the first occurrence of three letters followed by five numbers, with or without a space.”
If no match is found, ExtractRegEx() returns NULL.

Step 2: Remove the Space (If It Exists)

Replace(…, ' ', '')

If the original text contained ABC 12345, this step converts it to ABC12345.
The output is always consistent, which is crucial for joins, filters, and comparisons later on.

Step 3: Handle Missing Codes with Coalesce

Coalesce(…, 'NOT FOUND')

When no matching code exists, ExtractRegEx() returns NULL. Wrapping everything in Coalesce() lets us replace those NULLs with something meaningful: NOT FOUND. This makes the result:

• Easier to understand for users
• Easier to filter in the app
• Safer for downstream logic

Final Result

Clean, consistent, and analysis‑ready.

Why This Matters

Using regex in Qlik allows you to:

• Extract structured data from unstructured text
• Reduce manual data cleansing
• Build more reliable KPIs and dimensions
• Handle real‑world, messy user input gracefully

If you work with comments, notes, descriptions, or reference fields, regex is one of the most powerful tools you can add to your Qlik toolbox.