Data Warehousing Explained
Data Warehouses are increasingly used by enterprises to increase efficiency and competitiveness. Using Scorecarding, Data Mining and OLAP analysis, business value can be extracted from Data Warehouses. Generating positive return-on-investments (ROI) from Data Warehouses requires a blend of business intuitiveness and technical skills. This web site covers strategies and technologies that will enhance the ROI of Data Warehousing.

• Data Cleansing for Data Warehousing
  How important is Extract, Transform, Load (ETL) to data Warehousing?
• Introduction to OLAP
  Slice, Dice and Drill!
• Selecting an OLAP Application
  Minimizing risks in the product selection process
• Planning for a Data Warehouse
  Starting a Data Warehousing Project? Three words - Plan, Plan and Plan!
• Designing OLAP Solutions
  MOLAP, ROLAP, HOLAP and other acronyms!
• Introduction to Metadata
  Case study of an implementation in the insurance industry
• Integrated Data Mining and OLAP for MySQL
  Case study for using DAT-A in the retail industry for data mining. Also included in the article is an overview of a data center built on Linux boxes instead of servers.
• Evolution of Analysis - Microsoft's NetScan and Project Aura
  Data mining, OLAP and reporting combined!
• Data, Data Everywhere!!
  
• Future of Data Mining
  From obscurity to center stage
• Relationship Mining
  Data mining six degrees of separation
• Intelligent Data Mining
  Open source application for data mining on MySQL
• Text Mining for Fraud Detection
  Creating cost effective data mining solutions for fraud analysis
• Data Warehousing RFP
  Writing a Proper Data Warehousing Request for Proposal!
• Data Warehouse Design
  Design Methodologies of Kimball and Inmon...Plus a Third Way
• Data Modeling and Mining
  Modeling for data mining
• Data Life Cycle Management
  Evolution of Data in Enterprises
• OLAP Analysis
  Online Analytical Processing
• Text Mining
  This article gives an overview of Text Mining and also describes an application the author is developing for Text Mining
• Data Warehouse Project Management
  Listen, Listen, Listen to the Stakeholders