De-Hyping Big Data: Seeing It, Using It, Managing It

A conversation with Chris Johnson, Director, Scientific Computing and Imaging Institute; and Distinguished Professor, School of Computing, University of Utah; Jeanne Harris, Managing Director, Information Technology Research, Accenture Institute for High Performance; Kirsten Bay, President and CEO, Attensity; and Tim Mitchell, CEO, Dot AIN

We currently have more data inputs, storage, computing and analysis tools than ever and the amount of information the human brain can store is miniscule compared to amount of data that is out there. This creates not only challenges but also opportunities for the future.

Executives are now demanding that they not only have the information packaged together, but that the information is analyzed and tells them what to do. This creates an interesting challenge, as there is an increasing trend where senior decision makers are unable to fully understand the reasoning behind the analysis, which is driving their decision-making.  There was debate within the discussion as to whether or not the workforce was being properly prepared to understand this information. Several people thought that in order to properly use big data effectively you need to have an understanding of the analytics and game theory behind the information. Others argued that not everyone needs to have the in-depth knowledge behind the theory.

While discussing the importance of developing algorithms which can better analyze the data and apply it to the market it was determined that it is still important to write in hypothesis driven analysis. Several people had found that without this the algorithms were missing out on some of the most important data information which is overlooked when merely looking at sensical patterns. Finally it was predicted that by 2020 analytics of big data and algorithms would be a key part of all businesses.

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