We hear the term “big data” thrown around so much that it is difficult to imagine that prior to the mid-’90s, few businesses even knew what it meant. In case you’re still unsure, big data is any collection of data sets so large and complex that it is difficult to analyze using traditional data processing applications.
All companies should address data challenges to support decision-making or risk falling behind. Businesses are collecting, storing and analyzing more data than ever before, and the trend is continuing to gain momentum. However, it’s not who has the most data that wins. “There is a big data revolution,” says Gary King, director of Harvard University’s Institute for Quantitative Social Science. But it is not the quantity of data that is revolutionary. “The big data revolution is that now we can do something with the data.”
Since much has been written about descriptive and diagnostic analytics, we will focus on predictive and prescriptive analytics — technologies that will transform the finance function by providing forward-looking insights; aligning the enterprise to the optimal course of action; quantifying trade-offs fast and with a low cost of ownership; and increasing the ability to communicate and collaborate across functions. These transformative characteristics will lead to significant performance improvements.
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