Mastek modernizes a legacy healthcare data system with Databricks-powered Data Lakehouse
For TPAs, health plans, financial institutions, HCM platforms, and PEOs, fragmented data and lack of actionable insights hinder visibility into benefit usage, costs, and ROI. Disconnected systems, mismatched formats, and errors between claims, eligibility, and payroll slow decision-making and processes.
Mastek modernized the legacy on-prem data into a scalable Databricks lakehouse, improving performance, agility, and cost efficiency.
Client Snapshot
As a market leader in SaaS-based benefit funding and payment solutions in consumer-directed healthcare (CDH), our client, a US-based healthcare organization partners with health plans, TPAs, and financial services providers to deliver scalable, customizable solutions that integrates health and wealth management. A pioneer of innovative solutions (such as the first FSA debit card), it processes more than USD 6 billion in healthcare transactions annually and has consistently outperformed competitors by significant margins.
Challenge
With a strong focus on customer-centricity, the organization needed to enhance its ability to respond swiftly and effectively to evolving business and end-user demands. Agility, scalability, and modernization were critical priorities, yet several challenges stood in the way. The legacy on-premise systems could not support rapid data growth in a simple and cost-effective manner. The absence of self-service reporting limited business responsiveness, while the lack of a multi-tenant architecture and reliance on multiple fragmented databases created inefficiencies. High maintenance costs further strained operations, making it essential to move towards a flexible cloud architecture with automated processes and modernized data management.
Solution
The transformation was executed through a strategic migration from legacy on-premise systems to a modern Databricks-powered lakehouse architecture, structured using the medallion model-bronze for raw ingestion, silver for business-transformed data, and gold for analytics-ready aggregates and facts. As part of this implementation, logical data models were revamped and aligned with evolving source systems, while dimensional modeling was applied to support downstream reporting. Scalable workflows and ETL jobs were designed in Databricks, along with reusable frameworks and automated processes to ensure efficiency, consistency, and adaptability to future requirements.
In addition, new logical data models were created to meet reporting requirements, while existing models were updated to stay aligned with changing source systems. With the introduction of secure self-service reporting capabilities and modern tools, business teams were empowered to access faster insights, enhance scalability, and build a sustainable foundation for high-performance data operations.
Impact
Mastek’s transformational solution achieved a host of positive outcomes to enable the healthcare giant to outperform on its goals of performance efficiency, speed, scalability, agility, and cost efficiency, as follows:
- 3x improvement in ad hoc query response times.
- A 80TB to 1PB scalability with high data availability in handling consumer data growth.
- 16% reduction in annual OPEX for high cost efficiency.
- Detect mismatches between claims and eligibility data.
- Provide TPAs, health plans, banks with on-demand analytics. Seamless and uniform reporting, tailor benefit communications to member demographics and usage patterns.
- Forecast contribution patterns, detect under-utilized benefits.
- Aggregate all benefit account info into one interface.
- Recommend benefit usage tips based on spending patterns.
- Re-usable framework and modern tools with secure self-service reporting capability.
- Master Data Management (MDM) – single source of truth for member and account information. Standardize data definitions across all partner implementations.
- Automated compliance checks – flag expired eligibility or contribution limit breaches.
- Increase contribution and utilization rates resulting in higher transaction volumes and more fee revenue.
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