The Attunity Blog
The creation and consumption of data continues to grow by leaps and bounds and with it the investment in big data analytics hardware, software, and services and in data scientists and their continuing education. The availability of very large data sets is one of the reasons Deep Learning, a sub-set of artificial intelligence (AI), has recently emerged as the hottest tech trend, with Google, Facebook, Baidu, Amazon, IBM, Intel, and Microsoft, all with very deep pockets, investing in acquiring talent and releasing open AI hardware and software.
The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one--computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms.
The story of how data became big starts many years before the current buzz around big data. Already seventy years ago we encounter the first attempts to quantify the growth rate in the volume of data or what has popularly been known as the “information explosion” (a term first used in 1941, according to the Oxford English Dictionary). The following are the major milestones in the history of sizing data volumes plus other “firsts” in the evolution of the idea of “big data” and observations pertaining to data or information explosion.
Analytics is both the lifeblood and livelihood of digital native companies such as Google and Facebook which thrive by analyzing the data generated by their Web position to drive their access to and engagement with millions of people. This analytics dominance by the digital natives has been expanded by a number of older companies such as Apple which have successfully adapted to the digital economy. In response, companies in established industries have beefed up considerably their data collection and analysis activities. But how good are they in mining the data for new and profitable insights?
The third annual Burtch Works Study: Salaries of Data Scientists is out, documenting the continuation of a very favorable market for those with the sexiest job of the 21st century. However, the salaries of data scientists appear to be leveling off: Every job category except one (entry-level individual contributors) experienced a marginal single-digit shift in median base salary over the past year. Learn more.