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In this section of the Data Warehouse Buyer's Guide, you'll learn some of the reasons why organizations should build data warehouses, find out why data warehouse projects and implementations often take so long to complete, and get tips on ways to educate yourself on data warehousing concepts.


Data Warehouse Buyer's Guide Table of Contents:
Selecting the right data warehouse platform for your organization
How to evaluate data warehouse software in five steps
Commodity hardware aiding data warehouse appliance performance, costs
Why you should build a data warehouse
Workload management tools key to running busy data warehouses


I want to know more about data warehousing concepts. I have read that data warehousing projects take a long time and are not always commercially successful. What is the argument for a data warehouse, and how can I sharpen my data warehousing skills?

There are three questions to answer here:

  1. Why should a company deploy data warehousing?
  2. Why do data warehousing projects take a long time, and why are they not always successful?
  3. How can I learn more about data warehousing?

1. Why should a company deploy data warehousing?

There are many reasons for an enterprise to implement data warehousing (DW), such as competitive advantage, improving business operations and regulatory compliance. We should include data warehousing along with business intelligence (BI) and performance management (PM), both of which are built on data warehousing, as the IT enablers for many business-driven initiatives. Data warehousing and BI have remained as top priorities in CIO surveys over the last few years and were the top priority in a Gartner survey for 2007 spending.

2. Why do data warehousing projects take a long time, and why are they not always successful?

Data warehousing projects take time because they generally involve consolidating data from many sources, both internal and external, to an enterprise. This consolidation involves ensuring data consistency, integrity and quality. This process means talking to business groups across the enterprise, which is time consuming -- but worth it to ensure the right information becomes available throughout the enterprise.

You might have read surveys about the high failure rate of BI or data warehousing projects. Although those make for good headlines, the reality is that very few BI or data warehousing projects really fail technically. Rather, they fail to meet timeline or spending expectations. This failure is the result of project teams not really understanding what to do and project managers not being experienced enough in these projects to properly manage expectations and scope. That brings us to…

3. How can I learn more about data warehousing?

There are plenty of online resources from which you can learn about data warehousing and BI:

I would also suggest data warehousing and business intelligence training that explains the concepts, fundamentals and architectures involved in these projects. Too many people believe that data warehousing is just like the application development they did in the past, which is why so many projects are late and over budget. Training specific data warehousing and business intelligence tools is fine but you need to understand overall data warehousing and business intelligence for success.

Good luck!


Data Warehouse Buyer's Guide Table of Contents:
Selecting the right data warehouse platform for your organization
How to evaluate data warehouse software in five steps
Commodity hardware aiding data warehouse appliance performance, costs
Why you should build a data warehouse
Workload management tools key to running busy data warehouses

This was first published in August 2007

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