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Data warehouse automation works on the principles of design patterns. It comprises a central repository of design patterns, which encapsulate architectural standards as well as best practices for data design, data management, data integration, and data usage. [3]
Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
It is documented in the book: Building a Scalable Data Warehouse with Data Vault 2.0. [13] It is necessary to evolve the specification to include the new components, along with the best practices in order to keep the EDW and BI systems current with the needs and desires of today's businesses.
The Kimball lifecycle is a methodology for developing data warehouses, and has been developed by Ralph Kimball and a variety of colleagues. The methodology "covers a sequence of high level tasks for the effective design, development and deployment" of a data warehouse or business intelligence system. [1]
Ralph Kimball (born July 18, 1944 [1]) is an author on the subject of data warehousing and business intelligence.He is one of the original architects of data warehousing and is known for long-term convictions that data warehouses must be designed to be understandable and fast.
The earliest versions of dbt allowed analysts to contribute to the data transformation process following the best practices of software engineering. [4] From the beginning, dbt was open source. [5] In 2018, the dbt Labs team (then called Fishtown Analytics) released a commercial product on top of dbt Core. [6]
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