Data Warehousing ETL Checklist ETL (Extract, Transform and Load) is a key, and very complicated, component of a data management strategy. This high-level checklist of the most central issues will help you get started with this critical data warehousing issue. ETL — Extract, Transform and Load — is the process by which data from multiple […]
ETL (Extract, Transform and Load) is a key, and very complicated, component of a data management strategy. This high-level checklist of the most central issues will help you get started with this critical data warehousing issue.
ETL — Extract, Transform and Load — is the process by which data from multiple systems is consolidated, typically in a data warehouse, so that executives can obtain a comprehensive picture of business functions, e.g. the relationships between marketing campaigns, sales, production and distribution. It has been estimated that in any data integration project, ETL will consume 60 to 70 percent of the time and resources.
The process is complicated and has been the subject of numerous books. Anyone undertaking an ETL project for the first time will have to do some serious research. Here is a high-level checklist of the important topics.
The attached Zip file includes:
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