Modernizing ETL Workflows with DBShift™ Powered Databricks Migration

A leading global healthcare solutions provider needed to modernize its ETL environment to reduce dependency on costly legacy systems and accelerate data engineering. The company’s existing workflows were built on Informatica, a legacy platform that had become complex, expensive to maintain and it was time-consuming to migrate manually. 

To address these challenges, the organization chose Databricks as its new platform and partnered with Systech to accelerate the migration. Using its flagship DBShift™ product, Systech automated the conversion of Informatica workflows into Databricks-native pipelines. This automation eliminated most manual effort, reduced migration timelines and established a scalable foundation for modern data engineering. 

Business Needs 

The organization sought a faster, smarter way to modernize its ETL workflow and address the limitations of legacy systems. Its key priorities were to: 

• Scale Efficiently – Move to a high-performance platform capable of handling increasing data volumes and workloads. 

• Accelerate Delivery – Reduce the time to build, run and manage ETL workflows. 

• Minimize Manual Effort – Eliminate the resource – heavy task of manually rewriting Informatica workflows. 

• Ensure Accuracy and Reliability – Ensure converted workflows to deliver consistent, high-quality results. 

Systech Delivery 

The move to Databricks was powered by DBShift™, which automated the conversion of Informatica XML mappings with over 90% accuracy. This minimized manual effort and enabled the migration to be completed in under two weeks with minimal disruption to operations. 

Solution 

Systech implemented a structured approach to accelerate the company’s migration to Databricks: 

• Set Objectives – Collaborated with stakeholders to outline goals and success criteria. 

• Activated DBShift™ – Converted Informatica XML mappings into Databricks pipelines, eliminating most manual effort. 

• Validated Accuracy – Conducted testing to ensure migrated workflows delivered consistently with reliable results. 

• Ensured a Smooth Transition – Delivered a ready-to-use solution with a clean handover and no disruption to ongoing operations. 

Impact 

• Accelerated Time to Value – Automated conversion shortened the migration lifecycle and enabled completion in under two weeks. 

• 90%+ Reduction in Manual Work – Automation eliminated most rewrites, ensuring faster and more efficient delivery. 

• Improved Accuracy and Reliability – Validation ensured workflows delivered consistently with high-quality results.  

• Seamless Business Continuity – The migration was executed smoothly with no disruption to the ongoing operations. 

• Scalable Development – Established a strong foundation on Databricks to support future growth and evolving business needs. 

The migration not only reduced manual effort and improved accuracy but also established a scalable platform, positioning the organization for future analytics initiatives, broader modernization projects, and long-term business growth. 

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