ETL Fails = "Illegal Number of Inputs"

1. Timing/Latency Issues with Input Datasets

• Problem: If the input datasets are updated by upstream processes (e.g., data imports, other ETLs, or connectors), there might be a timing issue where the ETL is triggered before these datasets are fully refreshed or populated.
• Solution: Adjust the schedule of your ETL to run slightly later, ensuring that the input datasets have been fully updated. You can also check if there are any data delays by reviewing the update logs of the input datasets.

2. Empty or Delayed Data Inputs

• Problem: Occasionally, one or more of the input datasets might be empty or not updated at the time the ETL runs, leading to a zero-input error.
• Solution: Implement a check within the ETL to verify that input datasets are populated before processing. If the datasets are empty, the ETL could be set to delay or retry after a certain interval.

3. ETL Schedule Conflicts

• Problem: If the ETL or its input datasets are involved in other processes that run at a similar time, there could be a conflict that causes the ETL to fail.
• Solution: Review the schedules of related processes to ensure there are no overlaps or conflicts. Stagger the ETL schedule to avoid any potential conflicts.

4. Dataset Connection Issues

• Problem: There could be transient connection issues with the datasets, especially if they are sourced from external systems or connectors.
• Solution: Investigate the health and reliability of the connections to your input datasets. If possible, build in retry logic within the ETL to handle these transient issues.

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