Tableau to Power BI Migration for a Leading Medical Association

85%

Reduction in operation and licensing costs of the BI reporting tool

60%

Improvement in data model performance

95%

Reduction in spend on supporting NRT processess

Background

Our client is a not-for-profit that serves the academic medical community. They have been serving this community for nearly 150 years and are a trusted partner in medical education, health care, medical research, and community collaboration.

Challenge

The customer faced continually escalating licensing costs for running Tableau, approaching $1 million annually. The customer approached us to find a solution whereby they could better scale compute and licensing to demand.

Approach

We engaged with the customer to analyze the gap and understand what was missing. We then proposed a solution with cost estimates and ROI to determine if it was worth it. We laid out an implementation plan with needed infrastructure and timelines and then began executing.

Key results

Migrated dashboards for 2 customer facing portfolios. Eliminated anti-patterns within the dashboards and data models, improved performance, and improved supportability by the customer's team.

Developed more native and robust infrastructure to support the project. Implemented autoscaling, native NRT reporting, and an improved authentication and authorization facility.

Worked with the internal BI team to train them to support the new dashboards and infrastructure. Successful KT such that the customer is confident in supporting the new solution. Worked with the internal team such that they were able to resolve real world additional use cases with our guidance.

Benefits

We greatly reduced operational costs involved in maintaining the solution. We created a highly scalable solution that can support a large number of users while keeping costs low. We improved existing dashboards to make them more supportable, more uniform, and less complex. Our autoscaling, NRT, and authorization and authentication implementations can be expanded to any other dashboards in the customer's portfolio. Upgraded the customer's overall analytical solution and stack. Implemented dimensional modeling whereas previously the customer used flat, denormalized, and unscalable tables.