Advanced Data Pipeline and Real-Time Analytics Infrastructure for Healthcare Data Management

The client experiences high costs and inefficiencies in data aggregation, with data pipelines costing four times more than necessary and delays of up to two hours in data availability. Additionally, there is a lack of centralized data storage, making report generation cumbersome, and a skill gap in data engineering within the organization hinders effective data utilization.

A medium to large-scale digital health technology company focused on developing patient engagement platforms and clinical trial data collection systems.

• Reduce data infrastructure costs by at least 50% through optimized processing architecture.
• Achieve near real-time data synchronization with current delays minimized to approximately 2 minutes.
• Ensure 99.9% reliability and robustness in data pipeline workflows to support continuous operations.
• Implement a scalable, multi-layer data architecture (Raw, Trusted, Analytical) to deliver high-quality, normalized analytical data for business intelligence and reporting.
• Streamline data integration from various sources, including files, databases, and APIs, into a unified data platform.
• Enhance data security through encryption of sensitive information both in transit and at rest, combined with strict access controls.

• Distributed data processing engine to handle hundreds of gigabytes of data efficiently.
• Three-layer data architecture (Raw, Trusted, Analytical) for data normalization and high-quality analytics.
• Automated data pipelines orchestrated through a workflow management system supporting complex integrations from various data sources such as files, databases, and APIs.
• Real-time data synchronization with a latency of no more than 2 minutes.
• Robust data security measures including encryption, access controls, and compliance with healthcare data standards.

• External data sources such as file systems, relational databases, and APIs for clinical trial and patient data
• Business intelligence tools or dashboards (e.g., custom dashboards, BI platforms)
• Security and encryption services compliant with healthcare data regulation standards

• Scalability to accommodate growing data volumes and user access
• High availability and 99.9% workflow reliability
• Data security and privacy compliance, including encryption and access controls
• Performance optimization to achieve near real-time data processing with minimal latency
• Maintainability and ease of updates for evolving healthcare data standards

The deployment of an optimized, real-time data processing platform is expected to significantly decrease operational costs by at least 50%, improve data timeliness with delays reduced to approximately 2 minutes, and ensure high system reliability at 99.9%. These improvements will enable more accurate and timely reporting, enhance decision-making processes, and support the organization’s goal of delivering improved healthcare access and patient outcomes.