This category references to quality resources on the topic of data warehousing, described by Wikipedia as "a database used for reporting and data analysis. It is a central repository of data which is created by integrating data from one or more disparate sources. Data warehouses store current as well as historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons.
Delivers industry-based business intelligence, business performance management, data warehousing and data quality content.
Bill Inmon articles
Articles by the "Father of Data Warehousing".
Data Extraction and Ad Hoc Query of an Entity— Attribute— Value Database
Article outlining a method for ad-hoc querying of entity-attribute-value (EAV) warehouse models.
Data Mining Concepts and Techniques, 2nd Ed.
An introduction to data warehousing and data mining covering the full range of topics including normalization, cube space concepts, data mining algorithms, and machine learning.
Developing a Data Warehouse Architecture
A data warehouse architecture is a description of the elements and services of the warehouse, with details showing how the components will fit together and how the system will grow over time.
Five Steps to Optimizing BI and Data Warehouse Performance
General concepts in optimizing a data warehouse
Grandiose Data Delusions
A blog by Mike Pluta containing articles, tutorials, information and infographics about big data and related topics.
Kimball Group: articles and columns
The site gives access to Ralph Kimball and other Kimball Group members's columns and articles on data warehouse for the period 1995-2005.
Managing Current and Historical Views of Information in The Data Warehouse
Michael Jennings' article on managing current and historical views of information.
Teradata Magazine Online
Teradata Blogs provide an opportunity to speak directly and candidly with those interested in Teradata, data warehousing and analytics-based decision making
Big Data Technology Does Not Replace a Data Warehouse
Bill Inmon's review of DW and its relation to the recent popularity of Big Data. (January 10, 2013)
The Four Legs of a Successful Business Intelligence (BI) Project Team
A successful BI project team is like a four-legged table - each leg holds up its share of the weight. Remove one and the project wobbles. The four legs of a team are Project Sponsorship and Governance, Project Management, Development Team (Core Team), and Extended Project Team. (April 01, 2003)
Data Warehouse Quality Management
Laura Hadley examines ways in which organizations can think about quality in the data warehouse environment, as well as ideas for possible metrics to measure quality and extend warehouse value. (April 03, 2002)
How to do a Warehouse Assessment (And Why)
Arthur Moore and David Wells. The essence of data warehousing assessment is directed at refining the warehousing process and revitalizing the warehousing initiative. (August 01, 2000)
Managing Meta Data Within and Across Warehousing Efforts
Many organizations must manage multiple warehousing initiatives underway simultaneously and these systems will most likely be based on products from multiple data warehousing vendors, in the typical decentralized approach of most corporations. (August 01, 2000)
Last update:March 3, 2016 at 6:15:12 UTC