Interview with Chuck Kelley - Part II

Part two of the interview looks at some design decisions in building a warehouse as well as some of the tools available.

Interview with Chuck Kelley - Part I

An interview with a data warehousing expert Chuck Kelley with some views about the careers in data warehousing.

Column-Store Databases and DW Appliances

With data volumes exploding, conventional enterprise data warehouses are fast running out of headroom. Data warehouse appliances are starting to fill the gap, but the emerging category of column-oriented databases may offer a better option. The key to success is matching your application to the right product.

Hubs, Spokes and Buses: How to Get to a Better Data Warehouse

Are you frustrated by the inefficiency, rigidity and latency of a first-generation, hub-and-spoke-architecture data warehouse? Here's a six-step guide to evolving to a streamlined, robust Kimball Dimensional Bus Architecture that will reduce time to reporting, lower data latency, and deliver more detailed, analytically useful information.

Master Data

Data Stores

Kimball University: Handling Arbitrary Restatements of History

How do you cope with an executive's request to "bring back a time series of activity for all subscribers who were in platinum status as of X date," or "show me a time series of orders by sales region according to the sales organization as of Y"? Here's how data warehouse pros can cope with the common requirement to look back in time.

Implementing Common Reference Data in a Data Warehouse

This article provides an architecture and process framework for implementing common reference data in a data-warehousing environment.

Data is at the Heart of Enterprise-Wide BI and DW, Part 3

My online series of articles has been focused on the need for businesses to "get serious" about their approach to developing an enterprise business intelligence (BI) and data warehousing (DW) capability. When pursuing this capability it is important to adopt a holistic view, followed by disciplined investment and execution.

The Logical/Physical Challenge in Data Management

A challenge is presented for data managers