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Podium Data Case Study

Astellas Pharma

In less than 12 weeks, Podium Data helped Astellas Pharma US transform a slow, inflexible, maxed-out data warehouse into a secure, self-service enterprise data lake that gives analysts the data they need in minutes, not months. Results thus far have been nothing short of a miracle cure.


Marketing plans for new pharma products take data. Lots of it. Data that only comes from extensive analysis and modeling across multiple, variable scenarios. It’s data that marketing teams often spend many months acquiring. In 2014, Astellas Pharma US, a leading global pharmaceutical company, was in the process of doing just that when they realized their data warehouse simply couldn’t keep up with the team’s needs. To stay on the leading edge of an industry built on innovation, Astellas knew something had to change. And soon.


Podium found a way forward. In less than 12 weeks, the Podium team deployed a secure analytics data platform on a Hadoop cluster. Moving Astellas’ data closer to users in a secure, managed data lake gave teams self-service, on-demand access—in minutes, not months. The Podium platform automatically loads, encrypts, organizes and validates prepared data sets, enabling the analysis of 100 billion records from 50+ data sources. Better still, the software automatically publishes data to Astellas’ teams using simple, widely available tools. As a result, data is once again moving at the speed of Astellas’ analytics teams.


Less than six months later, Astellas is seeing just how significant Podium’s impact has been. Not only is all Astellas data now in one place, the entire data lake itself can be refreshed in minutes. Tasks that took six months in the past now take mere minutes. Even complex analytical calculations—like a 10-year time-series analysis of patient behavior—can be done in minutes, not days. All of which means that more and better information is getting to the people who need it most and who can do the most good with it. And it’s happening faster and easier than ever before.