How To Detect Duplicate Transactions with Using BigQuery

Google Analytics 4 (GA4) and Google BigQuery are powerful tools that increase e-commerce sites’ ability to understand and analyze user activity. However, in order to be able to analyze this data correctly, it is very important to maintain data integrity. In this blog post, we will see how to check for duplicate `transaction_id` values in GA4 data in Google BigQuery.

GA4 generates a unique `transaction_id` value for each e-commerce transaction. This ensures that every transaction is accurately tracked and analyzed. However, sometimes duplicate `transaction_id` values can occur due to technical errors or other reasons. This may adversely affect the data analysis and reporting processes.

Here is a SQL query to check for duplicate `transaction_id` values in BigQuery on GA4 data:

SELECT
event_parameters.key AS transaction_id,
COUNT(*) as count
FROM
`projectID.datasetID.tableID`,
UNNEST(event_parameters) AS event_parameters
WHERE
event_parameters.key = 'transaction_id'
GROUP BY
transaction_id
HAVING
count > 1

This query finds events that have the same `transaction_id` value and returns their count. In an e-commerce application, no rows are expected to be returned as a result of this query, as each transaction must have a unique `transaction_id` value. However, this query allows you to check if duplicate `transaction_id` values exist due to an error or other condition.

Remember, you should use your own BigQuery project, dataset, and table IDs instead of `projectID`, `datasetID` and `tableID` in this query.

This query allows you to quickly and effectively detect duplicate `transaction_id` values for maintaining data integrity and accurate analysis and reporting. This is especially important on large-scale e-commerce sites, as the occurrence of double `transaction_id` values can negatively affect the accuracy of the sales data and therefore the reliability of the analysis.

Google BigQuery and GA4 are powerful and flexible tools for data analysis. This query demonstrates the ability of these tools to preserve data integrity and detect duplicate `transaction_id` values. This allows e-commerce sites to analyze user activity more accurately and reliably.

Kadirhan Gozukoca