Looker Studio Function : REGEXP_MATCH
REGEXP_MATCH Function in Looker Studio – Complete Practical Guide
Category: Text Function
The REGEXP_MATCH function in Looker Studio is used to check whether an entire text value matches a given regular expression pattern. Unlike REGEXP_CONTAINS, which checks for partial matches, REGEXP_MATCH validates the full text against the defined pattern and returns TRUE or FALSE.
In real-world dashboards, this function is especially useful for data validation. Many datasets contain values like email IDs, phone numbers, order IDs, or system-generated codes that must follow a strict format. REGEXP_MATCH allows analysts to verify whether the data follows that expected structure.
From a BI perspective, this function is commonly used in calculated fields, filters, and conditional formatting rules. It helps identify invalid records, enforce naming conventions, and improve overall data quality. Since REGEXP_MATCH evaluates data row by row, it works efficiently for large datasets when regex patterns are written correctly.
Overall, REGEXP_MATCH is a powerful function when precision matters and you need strict pattern validation instead of loose keyword matching.
Purpose of REGEXP_MATCH Function
1. Full Text Validation
Ensures the entire text value strictly follows a defined format.
2. Data Quality Control
Helps identify invalid or incorrectly formatted records.
3. Rule-Based Classification
Used to apply business rules based on exact text patterns.
4. Format Enforcement
Validates standard formats like email IDs, codes, or reference numbers.
Type of Calculation & Practical Use Cases
1. Boolean Calculation
Returns TRUE or FALSE based on regex validation.
2. Calculated Dimensions
Used to create validation flags or classification logic.
3. Data Cleansing
Helps filter out incorrect or malformed text values.
4. Dashboard Accuracy
Improves reliability of reports by validating text inputs.
REGEXP_MATCH(text, regular_expression)
REGEXP_MATCH Function – Parameters Table
| Parameter | Type | Description |
|---|---|---|
| text | Text | The text value to be validated |
| regular_expression | Text | Regex pattern for full text matching |
How Does the REGEXP_MATCH Function Work?
REGEXP_MATCH checks whether the entire text value matches the provided regular expression pattern. If the full text satisfies the pattern, it returns TRUE; otherwise, it returns FALSE.
The function is case-sensitive by default, so patterns must be defined carefully. It evaluates each row independently, making it reliable for validating large datasets. If the text value is NULL, the function generally returns FALSE.
When Should You Use REGEXP_MATCH Function?
When strict format validation is required
When validating emails, phone numbers, or IDs
When partial matches are not acceptable
When enforcing naming or coding standards
When cleaning and validating raw text data
Examples of REGEXP_MATCH Function
Example 1: Validate Email Format
REGEXP_MATCH(Email_ID, "^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Za-z]{2,}$")
Example 2: Validate 10-Digit Mobile Number
REGEXP_MATCH(Mobile_Number, "^[0-9]{10}$")
Example 3: Validate Order ID Format
REGEXP_MATCH(Order_ID, "^ORD-[0-9]{5}$")
Tips & Best Practices
Use REGEXP_MATCH only for strict validation
Prefer REGEXP_CONTAINS for partial matching
Keep regex patterns readable and documented
Always test patterns with sample data
Avoid overly complex regex for better performance
Yes, REGEXP_MATCH is case-sensitive by default, so uppercase and lowercase characters must be handled properly while writing regex patterns.
REGEXP_MATCH validates the entire text, while REGEXP_CONTAINS checks only for partial matches within the text.
No, REGEXP_MATCH only returns TRUE or FALSE. Use REGEXP_EXTRACT if you need to extract matched values.
If the text value is NULL, REGEXP_MATCH usually returns FALSE and does not match the pattern.
Yes, but regex patterns should be simple and efficient to avoid unnecessary performance overhead.