The Rise of the Data Warehouse Mechanic

Anyone who owns a car knows the value of a trusted and knowledgeable auto mechanic. The need has become more critical during the pandemic. The availability and price of new and used cars over the past year is a huge issue. As a result, people are keeping their cars longer and driving them more instead of taking public transportation. When you combine more aging cars on the road with greater miles driven it’s easy to see why your local mechanic is backed up with work. The pandemic has given me greater appreciation for many things previously taken for granted. Hail to these mechanically gifted men and women who literally keep the world moving.

So, what does this have to do with a data warehouse? Plenty. Due to economic uncertainty and staff constraints, business owners are reluctant to start a new data warehouse project. Memories of budget overruns with previous implementations fail to build confidence in committing new capital. Meanwhile, data usage is growing exponentially while the infrastructure is aging. Sound familiar? Many people can’t trust their data so they resort to “duct tape” fixes, such as using spreadsheets to reconcile data or manual data entry due to missing functionality.

MetaGovernance specializes in second surgery – our term – for failing data warehouses which in most cases means leveraging the assets in place. True, there are times when it’s more cost effective to scrap a data warehouse and start over, but only as a last resort. Think of us as the data warehouse mechanics that get your data warehouse “back in alignment” so it performs as expected.

We typically get called in to help for one of two reasons: 1) data quality is in question; or 2) the regulators are at the door. The people who are responsible for managing the data warehouse – often the CIO and his or her team – work hard to solve their data quality problems. This is especially frustrating after purchasing and installing “surefire” solutions. Nothing gets senior management’s attention more than regulatory, audit or other serious data lapses. This requires an independent review.

No matter what drives the need for data remediation, the solution lies in sound design, a focus on data quality, and effective governance.

Building a new data warehouse consumes a vast amount of corporate resources for requirements and testing. In the next blog we are going to discuss what to consider when the data warehouse mechanic tells you it is time for a rebuild.