Published: 17 Jun 2013
When researchers at pharmaceutical giant Pfizer Inc. need a data mart to analyze the effectiveness of a proposed new drug, there's a good chance they'll run into Pat Saucier.
Saucier is in charge of the group that manages data warehousing and related technologies for Pfizer's scientists, researchers and assorted business users. His official title is, well, a mouthful, to say the least.
"I am the director of solution strategy, information architecture, for Pfizer's research and development worldwide regulatory safety and medical business intelligence group," he said dryly. "And for your information it does not fit on a business card."
Saucier has worked in IT for more than 25 years, focusing mainly on database development, and data warehousing -- and, more generally, on using information to solve business problems. He's seen a lot of things change over the years, with perhaps the most notable shift coming in how businesses approach the concept of data itself.
While Saucier and his team deal with complex technologies, they're always careful to keep the needs of the business front of mind. One way they accomplish this is by continually referring to internal users as "business technology clients."
"At Pfizer, we call it BT -- business technology -- because we never want to forget business with our technology," he said.
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He spent 14 years as a consultant with Vertex Inc., based in New Britain, Conn., and helped that management consultancy create a business intelligence (BI) group. At Vertex, he also focused on extract, transform and load development, data mart design, master data management (MDM) and information architecture.
Saucier has worked for Pfizer twice. The first time was through his consulting job at Vertex. He left that position in 2005 to lead a data warehousing group at General Electric. He returned to Pfizer as a consultant in 2006 and became a full-fledged member of the staff two years later. He worked as an MDM program manager and enterprise information architect before turning to his current focus on research-related data warehousing and BI. "All things data kind of fold under my purview," he explained.
Over the last quarter-century, Saucier has seen businesses gradually wake up to the notion that data needs to be managed as an asset, and that process has included a growing emphasis on MDM and data governance. For example, the early days of data warehousing focused largely on providing the business with decision support and reporting capabilities. While those things are still important, attention has now shifted to total information management, he said. As part of that, organizations have become more interested in clearly identifying where data is coming from, where it is going, how it is processed and how the business is using it.
Saucier uses the words information and data carefully, pointing out that they have two distinct meanings. Data is a mass of unorganized factoids in need of processing. Information is processed data presented in a useful context.
"Data people would think about databases and data structure. Information is that data that is used to make informed business decisions," he said.
The increased attention being paid to MDM and data governance is symptomatic of a desire among businesses' many moving parts to agree on a "single source of the truth" of information and, as a result, ensure greater consistency. Saucier cautioned, however, that arriving at that one source is an ongoing process that requires agility.
"It's a gradual approach to single sources of the information, and for me that gradual approach says, let's collect the data, let's organize the data and let's put it in an information model that can be used to make business decisions," he said. "Once we do that and we identify where our authoritative sources are for that piece of the data, then we can start having consumers of that data -- whether they be systems or business [users] -- now consuming the same data."
Saucier stressed the importance of data consistency, explaining that an organization must have consistent data before it can have high-quality data.
Data conformity "gives the organization a consistent picture of their data and then allows the business to define what high-quality data is, so that they're not saying, 'This is my data and that is your data. My data is better than your data,' " he said. "This is our data. We own the data and we govern the data."