Today, the issue is no longer about owning the most data but rather about how to gain the most insights from it. In short, how to turn data into insights, and insights into real business advantage. Data is pervasive. telling us everything. But do companies really know where to look? The reality is that turning mountains of data into valuable. practical and actionable analytics is not nearly as straightforward as people believe.
As per a recent study , on an average an individual organization will spend about $7.4M on data-related initiatives over the next twelve months , with enterprises investing $13.8M, and small & medium businesses (SMBs) investing $1.6M. 80% of enterprises and 63% of small & medium businesses (SMBs) already have deployed or are planning to deploy data sciences projects in the next twelve months.
While commentators routinely discuss the opportunities for the United States and many other developed countries to use algorithms to improve the lives of their citizens, the many opportunities for data to transform the developing world are less well-known.
Data Sciences vs Political Pundits: Electoral Predictions
While most people are usually made to think every US election would be very close (as many politicians and pundits wanted us to believe), prior to the election, a number of quants and statisticians would beg to differ and would predict it is anything but a “nail biter.” As in the last few days before Election Day, their models and simulations predicted that Obama would prevail with close to 99 percent certainty based on aggregated poll data, in the 2012 US elections.
Given today’s constant barrage of negative news media, harboring concerns about public safety is understandable. For many, the specter of crime hangs much heavier than the reality of it – the world is, on average, much safer today than in the past. This is, however, certainly not always the case across the globe. Things many of us might take for granted, such as a low likelihood of a burglary, or a responsive police force, are near non-existent in other countries, some of them similarly industrialized.