Pivoting Services to Improve a Client’s Data Ecosystem
The governance team of one of the nation’s largest bank-based financial services companies was badly siloed in its analytics capabilities. As it stood, the team members had no internal resources to design and deploy business intelligence tools for the multiple departments seeking data visualization capabilities. The client’s issue was compounded by the fact that an analytics solution was needed posthaste for the implementation of a highly visible enterprise-wide project.
As certified Tableau partners, our team of professionals stepped in with a proven strategy to expedite a Tableau deployment and training to assist the client with its resource needs. However, when we started building assets, it was discovered that there was a less than adequate backend data model which was causing reporting issues. In hopes of solving this problem quickly, the client “borrowed” a third-party SQL administrator from another project to help design and build a database to bring the data together. Unfortunately, in this context, the developer lacked the experience for an entire redesign from a data architecture perspective.
A national bank-based financial services organization needed to accelerate its data visualization capabilities and foundations for an upcoming, highly visible enterprise-wide project. While building dashboards, it was discovered that a poor backend data model was disturbing analytics and reporting capabilities and business processes. This would require a complete data architecture redesign.
The client’s third-party developer was solely building for a problem, as opposed to designing for the end goal. Picture a handful of untethered rooms built without hallways to connect them. This disjointed process keeps data siloed and fragmented. What the client needed was an entire house equipped with multiple rooms designed in such a way that they can seamlessly interact and have flexibility to adapt. Having that sort of data management synergy is what will allow the client to answer questions dependent upon many disparate sources, creating a single source of truth.
After an appropriate analysis and presenting a Proof of Concept to the client and employees, they could now see and fully understand its current data dilemmas. It was agreed upon to bring in one of our own data architects, as well as a technical support person, to deploy a strategy and to design a proper data model that would combine and validate data assets. This would allow for not only higher quality and more performant Tableau reporting, but also the delivery of automated alerts to maintain a level of data quality moving forward.
Our approach and goals included the incorporation of a Data Ideology architect and technical support into the project to design a data model that would cleanse and validate data assets. This change in strategy will allow for all reports and analytics created by the Tableau software to be of the highest data quality.
Our consultants were initially brought in to help this company with a Tableau deployment, as well as with training and dashboard design best practices. However, upon the discovery of troubling data management issues, we were compelled to pivot our response and services and advised the client on the advantage of a well-designed data model to assist with data quality issues.
As a result of our insight and work, our client now had a modern data management system in place to properly manage data assets and gain reassurance that information being pulled into Tableau reporting was valid. They will also benefit from a design and framework that allows for flexibility and change as the project grows and its requirements and opportunities change in the future.