Case Study: AMK Cambodia streamlines data integration and boosts performance with Etlworks

AMK Cambodia speeds data loading with Etlworks using SQL*Loader and parallel ETL

AMK Cambodia, a leading microfinance institution, faced significant data integration challenges. They needed to efficiently parse and transform highly complex XML data from their Oracle and Postgres databases into normalized tables for their data warehouse. Their existing tools could not handle these complex transformations or optimize the bulk data loads required for their high data volumes. They turned to Etlworks for a solution.

Etlworks implemented a robust framework that used JavaScript and externalized mapping files to dynamically parse the XML data. The solution utilized automatic partitioning for parallel data extraction and Oracle bulk loading with SQL*Loader for high-performance ingestion. This resulted in automated XML transformations, significantly faster data processing, and scalable workflows that reliably handled AMK's high data volumes, seamlessly synchronizing their data.

AMK Cambodia