In today’s data-driven world, companies operating in Germany and across the EU must comply with strict data privacy regulations, such as the General Data Protection Regulation (GDPR) and other local laws. One key requirement in many industries is the removal of user behavior data after a certain period to protect user privacy. This can include deleting user accounts that have been inactive for a specific duration.
The Problem: Removing Inactive Users Automatically
Many businesses store user login data, but regulations may require them to delete users who have not logged in within a specific timeframe—for example, 90 days. Manually managing this process is inefficient and error-prone, especially for large organizations.
To address this challenge, we can use Jedox ETL (Extract, Transform, Load) to automate the identification and deletion of inactive users. This ensures compliance while reducing manual effort.
Solution: Using Jedox ETL to Identify and Delete Inactive Users
Jedox ETL allows us to create a streamlined workflow to extract user login data, filter out inactive users, and delete them from the system. Let’s go through the process step by step.
Extract: Fetching User Login Data
The first step is to extract user login records from the database. Typically, the user table should contain fields like:
usernamelast_login(stored as a UNIX timestamp)
In the Extract step of Jedox ETL:
- Connect to the database where user data is stored.
- Retrieve
user_idandlast_loginfields.
Transform: Identifying Users Inactive for 90 Days
The next step is to calculate the UNIX timestamp of last_login and compare it with the current date in UNIX timestamp format.
Jedox ETL allows us to use a formula in the FieldTransform step to calculate whether a user has been inactive for 90 days:
Conversion of UNIX Timestamp to Readable Date
UNIX timestamps are stored as seconds since January 1, 1970. We convert it to a readable date using the function Today’s date in UNIX – LastLoginDate in UNIX to be more than 90days in UNIX which is 90x24x60x60:
This logic determines whether a user has been inactive for 90 days or more.
In Jedox ETL Table View, we apply a filter:
- Keep only users where
90Days == delete me.
3. Load: Deleting Inactive Users
Once we have identified the inactive users, we move to the Load step, where we delete them from the database.
Using Jedox ETL, we can:
- Run a DELETE Load to remove the inactive users:
- Schedule the ETL job to run periodically (e.g., once a day) to ensure compliance automatically.
Benefits of This Approach
✅ Regulatory Compliance – Meets German and GDPR data privacy requirements by ensuring that inactive user data is removed automatically.
✅ Automation – Eliminates the need for manual data cleanup, reducing workload and human error.
✅ Efficiency – Optimized ETL processes ensure smooth and fast execution, even for large datasets.
✅ Security – Ensures that sensitive user behaviour data is not stored longer than necessary.
Final Thoughts
Using Jedox ETL to automate user deletion processes helps businesses comply with regulations and improves data management efficiency. By setting up a robust Extract, Transform, and Load workflow, companies can ensure that user behaviour data is removed promptly, reducing legal risks and maintaining user trust.
Do you have any questions or need help setting up this process? Let’s discuss this in the comments! 🚀
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