The six crucial steps to follow when building a Data Warehouse

Having spent over 25 years working with customers on their data warehouses, there are few mistakes that I haven’t seen made during their construction. The reality in fact, is that many organisations underestimate the complexities of building a data warehouse – or at least, building the RIGHT data warehouse for their business needs.

Here are six crucial aspects to building a data warehouse that will help you avoid the many pitfalls along the way of its construction.

1. Set a BI strategy: before you even press the start button on any build project, you need to be sure what business information will be required from your data warehouse, now and in the future. This will form the basis of your BI strategy. If you don’t have a BI Strategy in place, you may end up investing a lot of time and money on the biggest white elephant your business has ever created.
2. Engage the end user: once a BI strategy is in place, ensure it really achieves what users expect from it. Often, users have a high-level idea of what they require but don’t fully understand all its implications. The only way to avoid extra, unnecessary development costs is to get to the bottom of user expectations at the start of the process. And this involves patience, understanding and effective communication. And, once in place, ensuring all users are properly trained in using the data warehouse will help in its being quickly adopted throughout the organisation.
3. Ensure high quality data: your data warehouse performance will only be as good as the data it receives and stores. In today’s business technology environment, it’s highly likely that it receives data from several sources – which leaves the data wide open to errors. Inconsistent data, duplicates, logic conflicts and missing data all create real challenges in ensuring the smooth running of any data warehouse and will affect the reliability of any resulting analytics.
4. Regularly test your data: once you have ensured the quality of your incoming data, the priority then turns to testing it on a continuing basis to ensure its continuing accuracy. This can be done by developing an effective Software Testing Life Cycle (STLC) and is the only way of ensuring your data remains fit for purpose.
5. Optimise performance: even with the best of foundations, most warehouses will need “tweaking” to optimise its performance. Think of it as finely tuning the engine of a performance car – there’s usually a refinement to be made here or there to get the result you want more efficiently.
6. Avoid spiralling costs: relying on your in-house team to build a new data warehouse might seem a good idea at the time. In fact, many organisations have lived to regret that decision as they see development costs spiral, sorting out and reshaping projects as they go. As you can see from the few points above, there are many issues to consider – and, as with all things, you don’t know what you don’t know. Calling in the experts at the beginning of your project is a wise investment, saving you both time and money, and ensuring you get the data warehouse your organisation needs.