That the world is awash in data is in no doubt. Less reliable is a widespread conviction that the folks who populate that world have a good handle on what to do with all of them. Which explains why a guy like Jian Pei deserves the accolades of which he’s currently in receipt.
Pei, a computing science professor at Simon Fraser University and a Tier 1 Canada Research Chair in Big Data Science, was selected this week as a 2015 Fellow by the world’s leading computing society.
The Association for Computing Machinery’s fellowship acknowledges Pei’s contributions to the foundation, methodology and applications of data mining.
As a renowned researcher in the areas of data science, data mining and big data, Pei has a special focus on mastering the algorithms for frequent-pattern data mining. Useful in a whack of applications, these fundamental calculations are of particular value to individuals involved in retail planning. With them, retail marketers charged with making sense of the millions of transactions and hundreds of millions of products sold every day get a prescribed route to strategic merchandising.
Among other things, Pei’s frequent-pattern data-mining research provides vital insight into what products customers most often buy in combination. Retailers use it to strategically arrange their merchandise—and drive sales in turn—in the most effective, hard-data-informed way.
It also gives them an understanding of which smaller items they can promote to leverage the sales of larger, bigger-ticket items.
Pei’s algorithms have been patented, adapted by industry and even used in textbooks.