Case Study: Community Health Plan of Washington Streamlines Data Integration with Etlworks

CHPW Optimizes High-Volume Data Reloads from SQL Server and Oracle to Azure Synapse with Etlworks.

Introduction

Community Health Plan of Washington (CHPW), a nonprofit providing health coverage for Washington residents, leverages Etlworks to efficiently ETL data from SQL Server and Oracle databases into their Azure Synapse data warehouse. Etlworks’ ability to handle frequent full database reloads with exceptional performance and reliability makes it a cornerstone of CHPW’s data integration strategy.

The Challenge

CHPW faced several critical challenges in managing their data integration workflows:

Frequent Full Database Reloads: Required the ability to reload entire databases regularly without impacting performance or data integrity.

Diverse Data Sources: Needed seamless integration with both SQL Server and Oracle databases.

Scalable Performance: Required a robust solution to handle large volumes of data efficiently.

Cloud Integration: Sought optimized workflows for loading data into Azure Synapse.

Traditional tools struggled to handle the frequency and scale of CHPW’s data reloads while maintaining efficiency.

Why Etlworks

CHPW selected Etlworks for its unique ability to address their integration challenges:

High-Performance Data Reloads: Delivered the capability to efficiently reload entire databases without bottlenecks.

Seamless Database Integration: Provided robust connectors for SQL Server and Oracle.

Optimized for Azure Synapse: Ensured efficient and reliable data loading into Azure’s cloud-native data warehouse.

Scalable and Flexible: Supported growing data volumes and evolving integration needs.

Ease of Use: Simplified the setup and management of complex ETL workflows.

The Solution

Etlworks implemented a high-performance data integration framework tailored to CHPW’s requirements:

Full Database Reloads: Designed workflows capable of reloading entire SQL Server and Oracle databases into Azure Synapse with minimal downtime.

Robust ETL Pipelines: Built scalable workflows for transforming and loading data into the data warehouse.

Cloud Optimization: Leveraged Azure Synapse’s architecture to maximize performance and cost-efficiency.

Seamless Integration: Unified SQL Server and Oracle data into a centralized data warehouse for reporting and analytics.

Results

Efficient Database Reloads: Achieved frequent full database reloads with exceptional performance and reliability.

Unified Data Ecosystem: Integrated SQL Server and Oracle data into Azure Synapse, creating a centralized data environment.

Enhanced Scalability: Supported increasing data volumes and evolving business needs with ease.

Improved Operational Efficiency: Streamlined workflows, reducing time and effort required for data integration.

Key Takeaways

High-Volume Data Reloads: Delivered efficient workflows for frequent full database reloads from SQL Server and Oracle.

Seamless Cloud Integration: Optimized data pipelines for Azure Synapse, ensuring cost-efficiency and performance.

Scalable Performance: Supported growing data volumes with consistent reliability.

Unified Data Workflows: Simplified integration of diverse data sources into a centralized data warehouse.