Data Warehousing Best Practices

Data warehousing is not a new technology by any means. But it is one of those more intimidating subjects to many folks that don't have the experience or exposure to them. I've spent the past several years working on various data warehouses and data marts in the Life Science's industry, and have a developed a few tips and techniques to avoid some of the most common problems. Lets face it, Data Warehouses have a higher than normal rate of cost overruns and even project failure rates than other systems. This is largely due to the fact that they are complicated projects with several focused and specialized teams that aren't always communicating well. So I've put together a list of these "best practices" and my company, Intrasphere, published them in a white paper. Which makes it a prime candidate for sharing here.

Now, if you are a data warehouse guru, and you are looking for bleeding edge approaches that will shake the earth as you read, don't bother. This white paper is written for project managers and IT managers that may not have tons of data warehousing experience, but are looking for some pragmatic and practical advice they can both understand and use.

Data Warehouse Best Practices

As always, I appreciate your feedback and comments.