Keynote Day 2 - HP Big Data 2015 - theCUBE
Channel: SiliconANGLE theCUBE
Date: 12/08/2015

4 myths surrounding Big Data | #HPBigData2015
by Amber Johnson | Aug 12, 2015 

Facebook is one of the heaviest users of Big Data analytics. During a keynote address at the HP Big Data Conference 2015, Ken Rudin, head of analytics at Facebook, broke down four common myths surrounding Big Data.

The first is that in order to have a Big Data system, you have to use Hadoop. Rudin asserted companies should focus on Big Data from the perspective of business needs, which will lead to a broader look at technology. Rudin said that Hadoop is not always the answer, and sometimes it is even the “wrong tool.” Facebook uses relational database technologies to extend its results, whereas it uses Hadoop to look though “mountains and mountains of data to find the gems,” including the historical data. Rudin recommended asking, “What technology is the best tool for the job?”

Big Data Does Not Always Provide Better Answers

Another misconception is that “Big Data provides better answers,” but Rudin repudiated this assumption by saying that Big Data leads to “more answers and deeper insight on data.” Rudin said that Big Data often results in “brilliant answers to questions that no one cares about.” He stated the best way to  better answers is not to throw Big Data at a problem, but to formulate better questions. Furthermore, the path to better questions requires the best people asking how to get solutions to business problems.

To that end, Facebook sends its people to a two-week “Data Camp” where they learn a common language on how to use data. This hits on the third myth Rudin covered: “that data science is a science.” 

Rudin commented that businesses must also look at the art side of data science. He claimed that only 50 percent of data science has to do with “how to use the tool” and the other 50 percent stems from “how to frame questions to answer with data.” Rudin said, “A good idea is like sandpaper; it can’t make a good idea, but it can shape it” through an understanding of the industry.

Lastly, Rudin spoke about the assumption that “actual insight is the goal of analytics.” He countered that results from that insight are the true goal. Rudin advocated that data scientists have to make sure that people act on your insight” by evangelizing your insight.

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