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A data warehouse is an environment that combines an integrated decision support database with software to perform extraction transformation loading processes from a variety of operational and external sources. These technologies are combined to support historical, analytical, and business intelligence (BI) requirements.
A business intelligence (BI) process collects, stores, and analyzes the data produced by a company’s activities. BI encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI produces reports, analysis, and other supports analytical best practices.
Introduction In the beginning were applications. And applications served the corporation well until there was a desire for integration of historical information. However, applications supported
Effective data warehouse development requires an iterative approach that results in a robust, well-defined and usable system for analytics. This article is excerpted from Data
Developing a process for cost justifying a data warehouse and metrics for measuring various costs associated with a data warehouse project are essential for success
Knowing how to measure success and failure, and qualifying results for a data warehouse or analytics project is essential for all project managers. This article
Fully architected solutions to data warehouse / analytics systems, not independent data marts, is the right way to ensure all the benefits of integrated data
Independent data marts create stranded, unusable data. Independent data marts can spread like a disease through an organization and must be eradicated. There is a
