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Jake Porway: "Data Isn't Just A Spreadsheet—It's Us, It's Our World"
Big Data | July 04, 2013

Jake Porway: "Data Isn't Just A Spreadsheet—It's Us, It's Our World"

"Most companies think that if you can just get hackers, pizza, and data together in a room, magic will happen," big data speaker Jake Porway laments. "This is the same as if Habitat for Humanity gathered its volunteers around a pile of wood and said, 'Have at it!'" Porway is the founder of DataKind, an organization that connects data scientists with not-for-profit companies. Big data promises to deliver a wealth of applicable information for solving pressing problems in society. But there's more involved in cultivating that data than simply hosting a 48 hour hackathon, Porway points out.

He admits that hackathons have their merit. But, in his post in Harvard Business Review, Porway shows that there are other ways to harness the data poised to transform the way organizations address social issues. At DataKind, they focus on gathering people together in "data dives" rather than traditional hackathons. These involve a collection of individuals working together who not only know how to harness the data, but can also understand the data itself. It's also crucial, Porway says, to set out clear problem definitions in advance and to be sensitive of the data that's uncovered. Without all of these elements in place, it's easy to lose sight of the goals of the data scouring. What's more, the data itself can be misconstrued or misused if it isn't put into the proper context.

"Data isn't just a spreadsheet or a database: It's us," Porway writes. "It's the people we care about. It's our world." Data scientists and experts in the data (those who know what that data means) have to work together. Otherwise, you're left with a social problem and no data. Or, an abundance of data that doesn't really apply to the social problem at hand. "Let's lay the foundation for their success by bringing together world-class teams to ask the right questions, collaborating on the best interpretations of the data, and striving, always, to be sensitive," Porway advocates. "Let's not just hack it."
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