Agility, Tools & Best Practices of ETL

  • ETL has evolved to support schema detection, as well as the ability to handle schema changes automatically to some extent.
  • When used with an enterprise data warehouse (data at rest), ETL provides a deep historical context for the business.
  • By providing a consolidated view, ETL makes it easier for business users to analyze and report on data relevant to their initiatives.
  • Organizations need both ETL and ELT to bring data together, maintain accuracy, and provide the auditing typically required for data warehousing, reporting, and analytics
  • Analyzing Source Data
  • Validation
  • Optimizing the ETL Solution
  • Error Handling, Logging and Alerting
  • Scheduling, Auditing & Monitoring ETL Jobs
  • ETL Auditing
  • Check for data anomalies beyond simply checking for hard errors
  • Capture and store an electronic trail of any material changes made to the data during transformation




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