I found the SAP BI Support Data Load Errors and Solutions

 Data loads in SAP BI can be smooth one day and frustrating the next. Whether you're dealing with delta updates, full loads, or master data transfers, errors are bound to happen. The key is knowing how to interpret them and respond quickly.

🔄 Common Data Load Errors I’ve Dealt With

1. Delta Update Failures

Sometimes, a delta load from one data target to another just refuses to complete. The request turns red, and the monitor shows a technical failure. In most cases, I’ve found this is due to:

• TRFC communication issues

• Locked records (often by users like ALEREMOTE)

• Corrupt or invalid data entries

My fix: I go into the monitor, delete the failed request, and reset the delta pointer in the source. Then I retrigger the InfoPackage. If it’s a full load, I delete the request and restart the job cleanly.

2. Batch Job Doesn’t Run or Abends

There are times when the master job doesn’t even start, or it crashes mid-way. This usually ties back to job scheduling tools like Maestro or changes in job definitions.

My fix: I coordinate with the BASIS team to check the job logs and scheduling tool. If it’s a Maestro issue, they handle it. If it’s a BI-side problem, I dig into the job variant and dependencies.

3. Database Space Errors

This one’s a classic: the system throws a short dump with something like “ORA-01653: unable to extend table.” It means the database ran out of space while trying to load data.

My fix: I raise a ticket to the DBA team to extend the tablespace. Once they confirm it’s resolved, I delete the failed request and rerun the InfoPackage. I also check ST22 for the dump details to ensure nothing else is lurking.

4. Deadlocks During Load

Deadlocks can happen when multiple processes try to access the same resource. Sometimes it’s due to SMON or other background processes interfering.

My fix: I contact the DB team to adjust the SMON schedule or free up the locked resources. Then I clean up the failed request and restart the load.

🧠 What I’ve Learned

These errors aren’t just technical—they’re signals. Each one tells a story about system health, data quality, or process timing. The trick is to listen closely and act fast. I’ve built a habit of checking the monitor regularly, keeping an eye on short dumps, and documenting every fix so the team can learn from it.