The space of data analysis demands powerful tools, and Looker Studio (formerly Looker Studio) is one such comprehensive tool that helps simplify complex data and reveal insightful patterns. Among its many features is the function COALESCE. This article unpacks the practical usage of COALESCE, its syntax, how it works, practical examples, limits and tips for effective use.
The function COALESCE in Google Data Studio is used to return the first non-missing or ‘non-null’ value found from a list of fields. COALESCE is particularly useful when working with datasets where some fields might contain null or missing values. Instead of leaving these values vacant or filling them with 'zero' which might skew analysis, this function ensures the data remains uniform and accurate.
The basic syntax of the COALESCE function is
where 'field_expression' represents a field or an expression that you intend to check for non-null values.
Note: All field_expressions should be of the same type.
COALESCE function does a consecutive sequential check on all field expressions stated in its syntax, until it comes upon the first 'non-null' value. Once it finds this value, it immediately returns it and stops its search operation further.
Let’s use sales metrics for this example. Suppose you lead a team of sales representatives and each of them is responsible for both physical store sales and online sales. However, some reps might achieve sales only from one source, leading to null values in the data.
Use the following formula:
This will ensure you capture the first non-null sales value for total sales calculation.
Results
The only restriction of the COALESCE function is that all field_expression arguments need to be of the same type. So, for example, you cannot use COALESCE with fields that are a mixture of numeric and text types.
COALESCE, if used aptly, can prove to be a strong tool to tidy your data and drive accurate insights into Google Data Studio.
