Kanwardeep Bachhal

A top-tier Pharma client relied on legacy Cognos reports that queried a live Argus Safety DB, resulting in severe performance lags and data silos.

To solve the issue, I architected an end-to-end ETL pipeline to migrate data from the Argus Safety application into a centralized data warehouse. I designed a star schema model to support high-performance reporting. I then migrated 60+ legacy Cognos reports to Power BI and built a suite of automated canned reports for regulatory monitoring.

The solution improved report speeds by 40%, eliminated production DB stress, and modernized the BI UI/UX.

I re-architected a legacy, slow-performing enterprise reporting environment to drastically improve data retrieval and dashboard loading times for a major client.

The client's business dashboards, built on IBM Cognos 10, relied on an underlying relational data model. Due to growing data volumes, report execution times averaged a slow 60 seconds per report, leading to severe drop-offs in user adoption and leadership dissatisfaction.

I overhauled the architecture by converting the relational model into multidimensional Cognos Dynamic Cubes. I configured the cube's advanced caching mechanisms, including data and aggregate caches, to optimize multidimensional analysis. To ensure seamless morning reporting, I designed automated, scheduled report triggers that pre-warmed the caches before business hours, eliminating query latency for end users.

The solution resulted in a 91% reduction in latency, cutting average report execution time from 60 seconds to five seconds. I delivered instant, interactive, multidimensional data exploration for decision-makers and automated cache-warming workflows to ensure high-performance availability during peak hours.