1. Establish what data warehouse software you need. The core set of tools: database; extract, transform and load (ETL); and business intelligence (BI). I also strongly suggest a data modeling tool. Some companies may also need to examine data cleansing software — but note that most of data quality is performed in the ETL code that you write.

2. Determine what you already have, or what you have standardized on database software. Also, are you using other tools, such as BI tools, with other applications? A word of caution, though: Make sure you have the expertise to use the software you already have in-house AND that people are happy with that software.

3. Develop a shortlist. There are a few ways to get this list: look at industry analyst research reports, i.e. Forrester or Gartner; see what is bundled with software you already have such as ETL capabilities bundled with your database or BI tool; ask peers; and read articles by “independent” columnists.

4. Create your evaluation criteria. If you’re a TWDI member, you will be able to find checklists that you could use as a start for your criteria. Try to avoid lengthy feature packed checklists, though, as you can easily lose sight of the forest for the trees. The criteria should be Does the tool work for what you plan to do? — not Is it the most feature-packed tool in the universe? Much of what these tools offer is mature technology that would satisfy most people’s evaluation criteria, so you should have more than one choice in each software category.

5. Perform the data warehouse software evaluation. Two words of advice: keep it short and if you can structure it as a Proof-of-Concept (POC) that can be used in your project, all the better.