Two UW-affiliated data-management companies make vast amounts of data manageable by providing analytical tools capable of parsing and summarizing large quantities.
The companies, Context Relevant and Trifacta, organize data through computer programs to make information gathering more efficient.
“Companies have more data than ever before,” said Christian Metcalfe, vice president of products and co-founder of Context Relevant. “So much data that they don’t know what to do with.”
Research of any kind produces huge amounts of data. Wading through the material proves a challenge to researchers and an opportunity to employ computing tools that can reduce the workload.
“There are many, many application areas across science, “ said Dan Weld, professor of computer science at the UW. “It just makes it that much easier and faster to analyze big data.”
This is the opportunity Context Relevant and Trifacta hope to seize.
Context Relevant aims to help companies employ that data to the most efficient and best ends with simple models that replace the need for more skilled analysts. Context Relevant’s Flexible Analytics and Statistics Technology (FAST) employs a popular data-mining source to build and execute computational models in seconds. Such rapid speeds can pose a sizable advantage to companies and academics.
“Academics have clamored for us to make some of our applications available to them,” said UW alumnus Stephen Purpura, CEO and co-founder of Context Relevant. “Our solutions help them analyze in minutes or even seconds what otherwise takes overnight or even days.”
Trifacta, on the other hand, aims to develop new interactive systems amplifying people’s ability to work with data, said Jeffrey Heer, Trifacta co-founder and associate professor of computer science and engineering at the UW.
“There are a variety of approaches here,” Heer wrote in an email. “Different organizations take different strategies. Some utilize cloud-computing resources, such as Amazon’s web services. Others … range from multiple machine clusters for storage and processing to full-blown data centers. Software run on these systems can also vary.”
Twitter, Facebook, and Google employ some of these systems already, and they are just a few of the companies with massive amounts of user-generated data, which, if analyzed, could prove a gold mine of information.
Facebook is the most obvious example, with the chance to craft personalized ads based on the millions of photos, likes, posts, and statuses pointing to each user’s particular tastes. Similar data opportunities have been looming on the tech horizon for years, with Purpura, among others, believing that “big data” represents an unexplored field ripe with promise.
“I had the idea roughly a decade ago,” Purpura said. “The rate of data storage was increasing rapidly.”
Purpura developed the idea for Context Relevant while studying political science at the UW. Advised by Weld and fellow professor of computer science Ed Lazowska, the company gradually took shape.
“My studies at UW exposed me to the huge challenges of dealing with significant amounts of data,” said UW alumnus Dustin Rigg Hillard, director of engineering for Context Relevant. “We let our customers process their data faster than they ever thought possible — and this is a huge leap forward for this field.”
Given the UW computer-science program’s growing presence in the entrepreneurial technology scene, Heer said the number of UW alumni at Context Relevant and Trifacta is bound to increase.
“The CSE department is world-class and made a number of impressive hires in the past year,” Heer said.
Reach reporter Garrett Black at email@example.com or on Twitter @garrettjblack
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