We have to clean up the table so we can produce accurate conversion rate reports. The worker process that writes event logs into the EventTracking has a bug that intermittently insert duplicate rows for any of the customer actions.įortunately, we can detect duplicate rows based on customer_id, event_name, and event_datetime columns.įor examples, 2 rows with exactly the same values in customer_id, event_name, and event_datetime columns are considered as duplicates. Such as install/download, purchase/install, purchase/download ratios.
We have an EventTracking table that tracks different customer actions so we can calculate various conversion rates The same techniques can be applied to other relational database management systems such as SQL Server, PostgreSQL, or Oracle. This post will go through the different ways we can use to find and remove duplicate data from the MySQL EventTracking table we'll be using for this demo. However, if we already have duplicate rows in existing tables, we'll need to clean them up to ensure data quality as the data will likely be used for downstream reporting. In addition, we should set up appropriate table constraints to check and prevent duplicate records. It's best practice to perform pre-processing validation checks during import to detect and eliminate these dupliacte rows.
Duplicate rows could exist in the data source we are importing the data from. It is common to face the issue of duplicate rows in database tables. MySQL - Find and Remove Duplicate Rows Based on Multiple Columns
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