Data warehousing is an essential concept to empower businesses to be able to report on key business information. Relational schemas do not support fast queries or the flexibility of being able to quickly slice and dice information by geography, time, product, and other important descriptive attributes.
This primer introduces best practices and rules of thumb when a business is faced with the challenge of building a new warehouse or rescuing a heavily siloed one. Examples are given of the design of a star schema and a popular open source ETL tool to load and manage the data marts.
Based on extensive data warehouse experience in financial services and retail, the author condenses a difficult concept into practical next steps that can potentially lead to savings in time and effort.
This primer introduces best practices and rules of thumb when a business is faced with the challenge of building a new warehouse or rescuing a heavily siloed one. Examples are given of the design of a star schema and a popular open source ETL tool to load and manage the data marts.
Based on extensive data warehouse experience in financial services and retail, the author condenses a difficult concept into practical next steps that can potentially lead to savings in time and effort.
