A global 125-year-old safety certification company, with offices in over 40 countries, identified the need to move toward a more performance-based, data-backed operational model.
The client invested in Power BI Premium and incrementally deployed 60+ Analysis Services Tabular models on premise to support dashboards and reporting across the enterprise. Lacking a centralized architecture vision for these models and a Data Warehouse architecture optimized to support them, the business relationship with IT became strained.
In addition, a more democratized self-service model was required by the business for operational analytics through a consolidated data model. A more consolidated model would relieve the maintenance burden from IT and support a more centralized version of the truth.
Launch leveraged an iterative development approach to assess, design, and implement a scalable and centralized data model, and did the following:
- Provided awareness of the gaps within the existing architecture and architected the foundation for the consolidated model
- Interviewed business owners to understand the important business processes and gather reporting and measures for delivering the consolidated data model
- Developed a backlog of prioritized user stories which were used throughout the development lifecycle
- Created a business semantic layer which served as the foundation of the new consolidated model that helped drive greater user adoption
- Developed, tested, and deployed a consolidated tabular model along with the proper security protocols to support business needs
Launch successfully partnered with client stakeholders to improve the business and data architecture and drive the implementation of a consolidated data model, thus creating a single source of truth for analytics
- Gained insight into how each business area interacts and leverages the analytics platform
- Improved access to data that was originally spread across 26 sources and was now in a centralized location
- Decommissioned several redundant dashboards by implementing row level security and trained developers in best practices
- Rolled out a new intake process for gathering analytics requirements which focused on actionable insights along with iterative design
- Updated platform architecture to increase storage efficiency and enhance user experience