Case Study: AMK Cambodia Simplifies Complex XML Data Integration with Etlworks

AMK Cambodia Streamlines Data Integration and Boosts Performance with Etlworks.

Introduction

AMK Cambodia, a leading microfinance institution, leverages Etlworks to efficiently ETL and CDC data from Oracle and Postgres databases into an Oracle-based data warehouse. By addressing the challenge of parsing and transforming highly complex XML data into normalized tables, Etlworks enabled AMK to build scalable, high-performance pipelines. Advanced features like externalized mapping files, automatic partitioning, and Oracle bulk loading with SQL*Loader ensured seamless, reliable, and efficient data integration.

The Challenge

AMK Cambodia faced significant challenges with their data integration workflows:

Complex XML Data Parsing: Required automatic parsing and transformation of XML data columns into normalized tables with regular columns.

Dynamic Transformations: Needed flexible transformations driven by externalized mapping files.

High Data Volumes: Extracting and processing data from multiple database partitions in parallel.

Performance Optimization: Ensuring high-speed data loading into the Oracle-based data warehouse.

Existing tools could not meet the demands of parsing complex XML data or optimizing bulk data loads.

Why Etlworks

AMK Cambodia chose Etlworks for its unique ability to handle complex transformations and optimize data integration workflows:

Advanced XML Parsing: Leveraged JavaScript and externalized mapping files to dynamically parse and normalize XML data.

Partition-Based Parallel Processing: Enabled automatic partitioning to extract data from multiple database partitions simultaneously.

Oracle Bulk Load with SQL*Loader: Improved data loading performance significantly, ensuring timely updates to the data warehouse.

Scalable Workflows: Designed to handle high data volumes with efficiency and reliability.

Comprehensive CDC Support: Seamlessly captured changes from Oracle and Postgres databases for near real-time updates.

The Solution

Etlworks implemented a robust and efficient data integration framework for AMK Cambodia:

Dynamic XML Data Parsing: Developed workflows to parse and normalize complex XML columns using JavaScript and mapping files.

Partition-Based ETL: Utilized automatic partitioning to extract data in parallel from multiple database partitions, improving processing efficiency.

Oracle Bulk Loading: Integrated SQL*Loader for high-performance data ingestion into the Oracle data warehouse.

Comprehensive ETL and CDC Pipelines: Built scalable workflows to synchronize data from Oracle and Postgres databases.

Results

Simplified XML Transformations: Automated parsing and normalization of XML data columns, reducing manual effort and errors.

Enhanced Performance: Achieved faster data processing and loading with parallel extraction and Oracle bulk load.

Scalable Data Workflows: Supported high data volumes with reliable and efficient partition-based processing.

Improved Data Integration: Delivered seamless and automated ETL and CDC workflows from source to destination.

Key Takeaways

Advanced XML Parsing: Simplified the transformation of complex XML data into normalized tables.

Partition-Based Processing: Enabled parallel extraction of data for improved performance and scalability.

Oracle Bulk Load Optimization: Delivered a significant boost to data ingestion speed using SQL*Loader.

Seamless CDC Workflows: Ensured reliable synchronization of data from Oracle and Postgres databases.

Scalable and Reliable: Handled high data volumes with efficiency and reliability, supporting AMK’s growing needs.

Ready to tackle your most complex data challenges? Discover how Etlworks can transform your data integration workflows. Start your free trial today or request a demo.