ETL TOOLKIT RALPH KIMBALL PDF

Developing the ETL system is challenging because so many outside constraints put pressure on its design: the business requirements, source data realities, budget, processing windows, and skill sets of the available staff. Yet it can be hard to appreciate why the ETL system is so complex and resource-intensive. Everyone understands the three letters: You get the data out of its original source location E , you do something to it T , and then you load it L into a final set of tables for the business users to query. With the wisdom of hindsight from thousands of dimensional data warehouses, a set of ETL best practices have emerged.

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Developing the ETL system is challenging because so many outside constraints put pressure on its design: the business requirements, source data realities, budget, processing windows, and skill sets of the available staff.

Yet it can be hard to appreciate why the ETL system is so complex and resource-intensive. Everyone understands the three letters: You get the data out of its original source location E , you do something to it T , and then you load it L into a final set of tables for the business users to query. With the wisdom of hindsight from thousands of dimensional data warehouses, a set of ETL best practices have emerged. Careful consideration of these best practices has revealed 34 subsystems that are required in almost every dimensional data warehouse back room.

The Kimball Group has organized these 34 subsystems of the ETL architecture into categories which we depict graphically in the linked figures: Three subsystems focus on extracting data from source systems.

Five subsystems deal with value-added cleaning and conforming, including dimensional structures to monitor quality errors. Thirteen subsystems deliver data as dimensional structures to the final BI layer, such as a subsystem to implement slowly changing dimension techniques. Thirteen subsystems help manage the production ETL environment. Reference Book.

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Data Warehouse ETL: The Kimball Approach

Register Description The extract, transform, and load ETL phase of the data warehouse development life cycle is the most difficult, time-consuming, and labor-intensive phase of building a data warehouse. A solid ETL system is reliable, accurate and high performant. The course focuses on the overall architecture and design of the ETL system. We drill into the critical processes within the ETL system that are often overlooked.

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