What is ETL (Extract, Transform, Load)?
Process of combining data from multiple sources into a database, including cleaning and structuring data. Essential for data warehousing. Used in business intelligence. Companies use ETL tools to prepare data for analysis.
ETL best practices include data validation, error handling, and performance optimization. Implement incremental loading, maintain data quality checks, and document transformation rules for efficient data processing.
Select ETL tools based on data volume, source compatibility, transformation needs, and scalability requirements. Consider factors like real-time processing capabilities, cloud integration, and maintenance costs.
Common ETL challenges include data quality issues, performance bottlenecks, and integration complexities. Address these through proper planning, monitoring, and automated error handling processes.
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