Cloud Modernization of Enterprise Data Platform

Based in the US, the client is a prominent academic hospital chain specializing in medical research, treatment, and clinical education.

Performance limitations and high latency caused by legacy reporting systems, specifically SSRS and SAP BO.

• Fragmented data across legacy on-premises systems, operational databases, and research applications.
• Excessive manual reporting effort required from IT teams to extract and synthesize operational and research insights.
• Lack of cloud scalability and remote accessibility across clinical and research data workflows.

We partnered with the client's in-house engineering team to design and deploy a cloud-based reporting architecture. The platform consolidates disparate research and operational data sources into a structured Databricks and Delta Lake pipeline before delivering insights via modern visualization tools.

• Data Ingestion Layer: Implemented automated batch ingestion to collect raw data from on-premises systems, operational databases, and research applications.
• Bronze Layer (Raw Data): Ingested raw datasets directly into Delta Lake managed by Databricks for reliable, scalable storage.
• Silver Layer (Refined Data): Cleaned and structured incoming data within Databricks to create validated datasets for intermediate analysis.
• Gold Layer (Business Aggregates): Processed refined data into high-performance business aggregates using Databricks and Delta Lake to power reporting.
• Data Consumption Layer: Replaced legacy SSRS and SAP BO tools with Tableau for streamlined, accessible data consumption across teams.

• Migration Accelerator: Reusable modernization framework to accelerate the migration of data and transformation.
• Lakehouse Foundation: Delta Lake as the data lakehouse for ad hoc exploratory analytics and Silver layer preparation.
• Processing Pipelines: Databricks pipelines for data transformation and Gold layer implementation.
• Metadata Governance: Unity Catalog for enterprise data governance and cataloging.

• Legacy Elimination: Successfully transitioned away from rigid SSRS and SAP BO reporting setups.
• Reduced Manual Overhead: Automated batch pipelines and transformed data layers significantly decreased manual effort for IT teams, driving over 55% increase in team productivity.
• Latency Reduction: Reduced data processing latency by 60% compressing query load times from over 45 minutes down to under five minutes.
• Cloud Scalability: Delivered a modern, highly accessible cloud infrastructure capable of scaling alongside enterprise growth.