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Enterprise Data Integration & Engineering for a Leading Health Data Services Company

February 8, 2025
Enterprise Data Integration & Engineering for a Leading Health Data Services Company

A global health data services provider, specializing in real-world evidence, pharmaceutical analytics, and clinical data management, faced significant challenges in integrating, processing, and scaling its multi-source healthcare data infrastructure. Their fragmented data environment made it difficult to consolidate and analyze massive datasets from electronic health records (EHRs), pharmacy claims, clinical trials, and insurance providers. Their legacy data engineering architecture struggled with:

  • Most data sources are disjoined and deliver output in siloed, making cross-functional analysis complex.
  • Legacy inefficient and slow processing pipelines were delaying clinical insights and compliance reporting.
  • Poor data governance was inconsistent, raising compliance concerns around HIPAA, GDPR, and 21 CFR Part 11.
  • On-premises legacy systems were expensive and unable to handle large-scale healthcare data growth.

The company needed a high-performance, cloud-native data integration solution with real-time processing, robust data pipelines, and a centralized, secure data platform for seamless analytics.

Engaged with strong partnership 

Our Global Data Engineering Team implemented a comprehensive, end-to-end data integration framework to unify and optimize healthcare data ingestion, transformation, and processing.

  • Enterprise Data Lake and Warehouse Implementation – Designed a centralized data Lakehouse (Azure and Databricks) to ingest, clean, and unify structured & unstructured data from multiple sources.
  • Advanced Data Pipeline Engineering – Built scalable ETL/ELT pipelines using Apache Spark, Kafka, and ADF to handle millions of healthcare transactions per second.
  • Real-Time & Batch Processing – Introduced a hybrid processing model, using streaming for real-time patient insights and batch for regulatory & compliance reporting.
  • Automated Data Governance & Compliance – Integrated encryption, tokenization, access control policies, and GDPR & HIPAA-compliant data anonymization.
  • AI-Powered Data Quality & Transformation – Deployed ML-based data validation models to detect anomalies, missing records, and inconsistent data formats.

Value realized 

Data processing 4X faster – Reduced data ingestion & analytics latency from hours to minutes, improving real-world evidence analysis for pharmaceutical companies.

More than 50% cost reduction – Cloud-based architecture eliminated on-premises costs, improved scalability, and optimized infrastructure spending.

Fully compliance readiness – Automated governance workflows ensured HIPAA, GDPR, and 21 CFR Part 11 compliance without manual intervention.

Unified, high-quality healthcare data – Enabled real-time insights for clinical research, patient outcomes, and drug efficacy studies.

Powering Healthcare with Seamless Data Engineering & Integration 

With our Global Data Engineering Team, we transformed a complex, fragmented, and high-cost data ecosystem into a high-performing, scalable, and fully integrated platform. Our expertise in real-time data engineering, AI-driven processing, and compliance automation empowers mid-to-large healthcare enterprises to turn raw data into actionable intelligence—faster, more securely, and cost-effectively.

Call to Action: Struggling with healthcare data silos and slow analytics? Let’s build a smarter, scalable, and fully integrated data solution for your business! Set up your free consultation with our engineering team.