Explain techniques of error handling - ignore , rejecting bad records to a flat file , loading the records and reviewing them (default values)?
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Answer / Manu Chaturvedi
Error handling in data warehousing refers to strategies used to manage errors or inconsistencies during the ETL (Extract, Transform, Load) process. Three common techniques are: 1) Ignoring errors - skipping rows with errors and continuing the processing. This can lead to data loss if errors are not addressed later. 2) Rejecting bad records - stopping the ETL process when an error is detected and discarding the entire row or record containing the error. 3) Loading the records and reviewing them - loading all records, including those with errors, into the data warehouse for further inspection and correction by a data analyst. Default values can be set to fill missing or invalid data, but care must be taken to ensure they are appropriate and do not compromise data quality.
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