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Managing Exceptions

Managing exceptions is an important step in the ETL process to fix errors and keep data accurate. When a record doesn’t meet the required rules or criteria, it is flagged as an exception.

The basic process in managing the exception are as follows:

  • Detect and Flag: Exceptions are identified during validation checks at different stages of the ETL process. When data fails to meet rules or requirements, it is flagged for review. For example, a loan record with a negative amount might be flagged as a business rule violation.

  • Log Exceptions: Flagged records are logged in an exception table or file. This log contains key information about the error, such as:

    • Record ID: The unique identifier for the problematic record.
    • Error Type: The category of the issue (e.g., format error, missing field).
    • Description: Details about why the record failed validation.
    • Timestamp: The time when the error occurred. This log provides a centralized view for analysing and resolving issues.

  • Isolate Invalid Records: Exceptions are separated from valid data to prevent them from entering the next stage of the ETL process. This ensures that errors do not contaminate the data in the staging area or in the data warehouse.

  • Analyse Root Causes: Exception logs are analysed by analysts / business experts to understand why the errors occurred. This step helps identify patterns and determines whether the problem stems from the source data or not.

  • Correct Errors: The errors are resolved either manually or through automated processes. For example, a missing Loan ID might be filled in using external data, or invalid date formats might be corrected through tools.

  • Reprocess Corrected Records: After corrections are made, the records are reintroduced into the ETL workflow for validation. If they meet all requirements, they proceed to the next stage, otherwise, they are flagged again.

  • Refining Validation Rules: If similar exceptions occur frequently, the validation rules are adjusted to catch and handle these issues earlier in the process. For instance, adding stricter range checks in the stage table can prevent unrealistic loan amounts from passing through.

We have now covered the steps to manage exceptions. Next, let us explore the types of exceptions, focusing on active and suppression exceptions and how they are handled in ETL workflows.