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Real-Time Data Infrastructure Modernization for eClinical Platform

sombrainc.com

Medical

Information Technology

Business services

Business Challenges in Data Processing and Reporting

The client faced excessive data pipeline costs (4x over budget with 70% effectiveness), 2-hour data aggregation delays, inefficient report generation processes due to decentralized data storage, and lacked in-house data engineering expertise to address these issues.

About the Client

Digital health solutions provider for pharmaceutical, biotechnology, and healthcare industries

Project Goals for Data Infrastructure Modernization

Reduce data infrastructure costs by 50%
Enable near real-time data synchronization (≤2 minute delays)
Implement centralized data storage for BI/reporting
Achieve 99.9% data pipeline reliability

Core System Functionalities Required

Distributed data processing with Apache Spark
Three-layer data architecture (Raw → Trusted → Analytical)
Automated data pipeline orchestration with Apache Airflow
Real-time reporting capabilities via Sisense/Holistics integration

Target Technology Stack

AWS Cloud Infrastructure

Amazon S3 Data Lake

Amazon Redshift Data Warehouse

Apache Spark on AWS EMR

Apache Airflow on AWS MWAA

Required System Integrations

File-based data sources
Relational databases
RESTful APIs
BI tools (Sisense, Holistics)

Critical Non-Functional Requirements

Horizontal scalability for hundreds of gigabytes of data
End-to-end data encryption (in transit/at rest)
Strict data access control policies
High-availability pipeline architecture

Expected Business Impact of Data Infrastructure Modernization

Projected 50% reduction in infrastructure costs, 2-minute data latency enabling timely decision-making, 99.9% pipeline reliability for uninterrupted operations, and centralized data governance to streamline analyst workflows.