/ The Data Warehouse Dilemma

As head of client services, I get to partner with our customers who are trying to solve real problems with Domo.

A lot of their action is driven by end-user observations: our reporting is too difficult to use, too non-existent, too slow, too limited, too ugly and so on. But we also work with quite a few companies who have made a great investment in traditional business intelligence and are now running into some serious capability limitations.

One example is the (loud announcer voice) all-powerful data warehouse. In theory, it’s the perfect BI tool: a central repository that can capture all of your data from all of your systems around the organization, which is then leveraged by magical tools to create scheduled and structured reports and the kingdom is saved. Unfortunately, the reality most often falls far short of that lofty promise. While a data warehouse does serve an important purpose, by providing a hub for data from core applications, there will always be crucial data that falls outside the normal reporting model. I’m talking about the ad-hoc pipeline report, the rogue accounting spreadsheet, the third-party report that came in via email and the like.

Even the most sophisticated companies have only been able to coerce 70 to 80 percent of their business data into the data warehouse. And while I’m not trying to diminish that accomplishment, I am acknowledging that there’s a lot of data, structured and unstructured, still floating around underutilized in the organization. You simply are not able to answer all the critical business questions without considering the additional data. Many of our customers are acknowledging that too.

This is why Domo advocates a very different philosophy: accept the fact that your data warehouse will never be complete (Gasp!… Is someone getting fired?). As I said earlier, a data warehouse is a very valuable tool, but it’s important to recognize what it does well and what it does not do well. Rather than adopting a witch-hunt mentality on “non-blessed” data sources, you will be far more successful if you can accommodate them. And that requires a solution that easily expands beyond the core data warehouse, allows end users to easily integrate a myriad of data sources into the business conversation and doesn’t require a massive automation and capture project. This approach is one reason Domo has been garnering so much attention lately.

If you’d like to know more on this subject, I’d encourage you to download the Domo executive brief “The Data Warehouse Dilemma”, which discusses an approach to BI that both embraces and mitigates the limitations of a traditional data warehouse.