Enterprise data warehouse cloud implementation provides financial and operational insights.
A fast-growing solution provider of Protected Health Information, had several disparate data systems capturing performance metrics, invoicing/payment data, payroll data, patient data, and more making profitability reporting and operations optimization difficult.
To create a single source of truth, the organization was looking to create an integrated, robust, flexible data warehouse (DW). The DW would incorporate the necessary checks, balances, and reconciliation to ensure the data is accurate and trusted and would have to be designed to support performance measurement, profit analysis, and self-service reporting. But with so many overlapping sources of data, it was going to be a challenge to deliver.
The healthcare information solution provider engaged MNP to design and develop a cloud-based, scalable enterprise data warehouse leveraging the Microsoft Azure platform. To expedite early business return on investment, MNP divided the project into 3 phases of data load/transformation for the DW:
To kick-off the project, MNP facilitated a series discovery and design sessions, focused on reviewing and analyzing the current systems and data pitfalls. These learning would be transformed into a functional requirements document that would inform the modern data warehousing solution and impact the rest of the project.
MNP put the execution plan into action, prioritizing key initiatives (data accuracy, reporting, etc.) and return on investment. Leveraging Microsoft Azure Data Warehouse and Power BI as the chosen solution, due to their seamless integration capabilities, unified analytics platform, and powerful insights and applications, MNP worked closely with the healthcare information solution provider’s technology and business groups to rapidly build out the solution.
Before going live, during validation and user acceptance testing, the solution began to demonstrate value. Having data from different siloed systems centralized in a single enterprise data warehouse and the tools to support information analysis, facilitated the discovery of critical disconnects between line-of-business solutions. As a result, the interpretation of business definitions were challenged and refined and, where necessary, source systems were tweaked to align with enterprise expectations resulting in a more cohesive ecosystem.
With solution having just gone live recently, the healthcare information solution provider is looking forward to increased efficiencies and enhanced performance over the coming months.