The Life Science industry is no exception, so I recently took the opportunity to interview Chris Ferrara and find out if there really is a prescribed alternative to the ailing data warehouses of old.
David: Let’s start with an introduction! Chris, can you share your background in the Life Science industry and a little about your current role at Qlik?
Chris: I spent the great majority of my career in consulting. I worked for companies like Ernst & Young and ISA Consulting, where I specialized in enterprise intelligence and data warehousing. As a consultant, I worked for several pharmaceutical, biotechnology, and medical device companies. Now at Qlik, I work in our Industry Solutions team where I help Life Sciences customers and prospects to see where the industry is going and understand the “art of the possible” with modern analytics.
David: Before we jump to a diagnosis and prescription, how would you describe the core challenges many Life Sciences businesses face in the data landscape?
Chris: Information is the basis of every decision we make and yet for an industry so dependent upon innovation for its success, we often find ourselves relying on legacy practices to gain access to data. There is no changing the fact that data needs to be collected, integrated, cleansed, and optimized before it can be made available. But it’s a bold new world out there and it’s moving fast! For many, the approach to accomplish those tasks has been transformed and the traditional data warehouse simply cannot keep up. In fact, I would even argue that the concept of an enterprise data warehouse is fading fast.
David: What do you think has led to these changes and the impact companies face when trying to keep up?
Chris: Everything from how and where data is created and stored to how information is consumed has changed dramatically in the past few years. Mergers and acquisitions have left us with multiple diverse systems and repositories of data. Many of our information assets, such as physician notes, clinical records, vendor agreements, and invoices have been digitized, leading to various formats and structures of information. Advancements in sensors and connectivity now allow us to connect directly to internal and external devices to capture massive amounts of data. With the growth of cloud and collaboration with strategic partners, data is now coming from many places that extend far beyond our companies four walls.
The impact of all these changes in the data landscape are far reaching – regardless of the technology we choose, there is no single data repository, no data warehouse, no data lake or data garage that can hold all the data we need to be competitive. To make things worse, the whole landscape is a moving beast; even if a data lake is created, it would only be ‘complete’ until the next merger or new data source came along.
David: Let’s talk about the human impact, how do these changes and advancements affect the way we use data and the expectations we have?
Chris: The way we work and interact with data has fundamentally changed in all industries, not just Life Sciences. It is no longer just data scientists and statisticians that need data to do their jobs, it is all people including executives, sales reps, clinical operations, supply chain analysts, quality engineers, scientists, external partners, and sometimes even machines! Consumers who would have been happy with standard reports are now more advanced and their expectations of data availability have increased. They look for self-service data exploration and visualization capabilities in order to consume and interpret the variety of data that supports their role and the timeframe they need it.