Overview
Organizations need to drive innovation to stay competitive in a rapidly changing market. Modern data architectures provide a foundation for analytics and innovation but modernizing complex legacy data warehouse in the cloud presents a major challenge due to significant differences in ecosystems.
AWS Glue, a serverless data integration service, optimizes data lake architecture and addresses key data challenges. Bitwise uses the right combination of automation tools and migration experience to convert DataStage ETL to AWS Glue, solving the trickiest part of modernization.
Proven ETL Migration Methodology
- Assessment – we use our Automated Source ETL Analyzer tool for detailed assessment of your DataStage jobs. Deliverable is migration strategy and roadmap with optimal solution architecture using our knowledge base and best practices.
- Code Conversion – we use our Automated ETL Converter tool with extensive library of mappings and workarounds to convert DataStage code to AWS Glue. Our conversion report identifies areas where manual rework is required, which is handled by our team of experts.
- Testing & Validation – validation is the most important (and most overlooked) step of migration. We use our ETL Validation Framework of automation utilities and data quality frameworks to accelerate testing and certify the converted code.
Our model is to offer risk-free services engagement to convert the DataStage jobs with fixed time and cost using our automation tools to accelerate the conversion and our expert team to ensure code is optimized for the new environment.
We take on a scope of work defined by number and complexity of ETLs to be migrated and deliver fully converted, unit tested code for production implementation and testing.
Highlights
- Automation across entire migration lifecycle (Assessment, Code Conversion, Testing & Validation)
- Accelerated conversion with extensive library of mappings and workarounds supported by knowledge base and best practices for architecting optimal solution in AWS
- Average 40-50% reduction in Migration Time and 50-60% reduction in Migration Cost
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