Modernizing Pharmaceutical Data Pipelines with DBShift™

With a global presence and a major role in advancing the healthcare, this leading biopharmaceutical company relied on Informatica BDM pipelines to manage and process complex datas. To enable next-generation analytics, the company identified Databricks as its target platform. However, the existing BDM pipelines had become deeply embedded and increasingly difficult in scaling, leading to challenges with efficiency, data quality and the ability to meet evolving business demands. 

Migrating more than 5,000 pipelines to Databricks was estimated to take over a year if done manually. This approach would have been costly, time consuming and risky for business-critical operations. The company required a safe and efficient way to modernize its data foundation without disrupting ongoing processes. 

To address these challenges the organization partnered with Systech to take an automation-led approach. With the DBShift™ product, Systech migrated pipelines from Informatica BDM to PySpark on Databricks within a month and saved over 80% of the overall time and cost. The migration achieved more than 90% accuracy which reduced the risk, minimized manual effort and provided the company with a strong and scalable foundation for future modernization. 

Business Needs 

The company required a faster, safer way to modernize its complex pharmaceutical data pipelines while maintaining accuracy and efficiency.  

To support these goals, the team aimed to: 

• Scale Efficiently – Move to a high-performance platform capable of handling growing data volumes and complex workflows 

• Reduce Manual Effort – Minimize the labor-intensive work of rewriting deeply embedded BDM pipelines 

• Ensure Accuracy – Maintain data integrity and reliability during migration to prevent disruption to critical operations 

• Validate Automation – Demonstrate that an automation-led approach could deliver consistent results for enterprise-scale workloads 

Systech Delivery 

The company partnered with Systech to accelerate migration and reduce time-consuming manual work. Using DBShift™ product, Systech automated the conversion of BDM pipelines to PySpark on Databricks, ensuring accuracy and reliability. The team validated the migrated pipelines, monitored performance and completed the initial migration with minimal disruption to critical pharmaceutical operations. 

Solution 

Systech took an automation-led approach to modernize the company’s BDM pipelines and accelerate migration to Databricks: 

• Analyzed Pipelines – Used DBShift™’s Source Profiler module to automatically scan all Informatica BDM jobs, generating detailed insights on pipeline complexity and helping estimate migration effort, time, and cost. 

• Activated DBShift™ – Automated the conversion of BDM pipelines to PySpark, reducing the manual effort and speeding delivery. 

• Ensured Reliability – Verified that all the migrated pipelines are supporting the ongoing pharmaceutical operations without any disruption. 

• Enabled Seamless Transition – Delivered a ready-to-use system, allowing the teams to continue the operations smoothly. 

Business Impact 

• Achieved over 90% Accuracy – Ensured a reliable pipeline performance through high conversion and validation accuracy. 

• Reduced Risk and Manual Effort – Minimized hands-on work and maintained continuity of critical pharmaceutical data pipelines. 

• Built a Scalable Blueprint – Established a foundation for broader Databricks migration and future analytics growth. 

The company’s migration to Databricks using the DBShift™ product delivered over 90% accuracy, streamlined operations and positioned the business for scalable, high-performance analytics initiatives. 

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