Industry: Healthcare (Eyecare)
At a glance: MyntiQ Tech built an enterprise data warehouse and analytics platform for a U.S. eyecare organization with 550+ practices. It standardized 300+ KPIs, delivered 70+ role-based dashboards, and used a StarRocks OLAP database to bring queries from minutes to seconds.
Overview
This case study details the development and rollout of a large-scale enterprise data warehouse and analytics platform for one of the largest eyecare organizations in the United States. Operating across more than 550 practices nationwide, the platform unified operational, clinical, marketing, and financial analytics into a single, governed digital environment.
Business Problem
The organization faced severe reporting bottlenecks:
- Operational, clinical, and financial data was decentralized across 550+ practices, each running its own reporting logic.
- KPI definitions varied by region and division, making enterprise-wide performance comparison unreliable.
- Reporting cycles were slow, depending on manual exports that lagged business reality by weeks.
- The legacy database infrastructure could not support the reporting requirements of 300+ clinical and financial KPIs or handle new acquisitions.
How MyntiQ Tech Helped
MyntiQ Tech built a robust data warehouse and analytics layer:
- Enterprise Data Warehouse: Created a centralized data warehouse with standardized dimensional models to unify clinical and operational data.
- High-Performance OLAP: Implemented a StarRocks OLAP database to enable sub-second query speeds across multi-million row datasets.
- Governed KPIs: Standardized and operationalized 300+ KPIs spanning clinical performance, marketing ROI, supply chain, and revenue cycle management.
- Role-Based Dashboards: Designed and deployed 70+ interactive, role-based reports tailored for practice managers, regional directors, and executive leadership.
Business Outcomes Delivered
- Created a single source of truth for 300+ KPIs, aligning operational definitions nationwide.
- Reduced query execution times from minutes to seconds, improving user engagement and decision speed.
- Shifted reporting latency from weeks to near real-time, allowing clinics to adjust operations dynamically.
- Built a highly scalable data infrastructure that supports new practices without performance loss.
Frequently Asked Questions
How do you standardize KPIs across hundreds of healthcare practices?
MyntiQ Tech built standardized dimensional models in a central data warehouse and governed 300+ KPI definitions, so every region and division measures performance the same way.
How fast can an enterprise healthcare data warehouse be?
With a StarRocks OLAP database, queries on multi-million row datasets dropped from minutes to seconds, and reporting moved from weeks of lag to near real time.
Can the platform absorb new acquisitions?
Yes. The infrastructure was built to add new practices without losing performance.
Modernizing healthcare analytics? Talk to MyntiQ Tech or browse more case studies.