Data Science Fuels Information Analytics

Data science is the underlying process of most Big Data projects because it is widely recognized as a sensible activity for businesses that are looking to improve bottom-line functionality. In the past several years, data science has gained momentum due to several emerging trends, including the fact that companies now recognize that analyzing complex information can lead to substantial returns.

In a recent Inside Analysis report, IT expert Robin Bloor highlighted some of the drivers behind the data science movement, noting that there is "gold in the data." In many cases, organizations embrace enterprise analytics with the same tactics they used in the past. This tendency has prevented many organizations from experiencing the full return that could be associated with comprehensive Big Data projects.

Fortunately, progressive firms are recognizing that using sophisticated Hadoop and other open-source analytic products can be more beneficial than taking a run-of-the-mill approach to Big Data, Bloor asserted. As these complex solutions mature and evolve alongside an increasingly aware business world, decision-makers can take a more holistic approach to data science to reap the substantial rewards associated with mining massive volumes of information to find meaningful insight.

The big push
Although the knowledge of advanced analytics is encouraging enterprises to deploy data science initiatives, Bloor noted that the cloud is among the top drivers behind the movement as a whole. Unlike traditional IT environments, cloud infrastructure services enable decision-makers to quickly provision and launch Big Data projects with little to no wait time.

Meanwhile, the cloud landscape as a whole has matured more recently, meaning enterprises can accelerate their Big Data initiatives without worrying about information security or other concerns of the past. A separate Gartner report highlighted the growth of the cloud computing landscape, noting that the market for public services is expected to grow more than 18 percent in 2013 to generate $131 billion in revenue. This forecast is evidence that spending on the cloud will continue increasing in the coming years, which will likely contribute to the evolution of data science.

In the coming years, organizations will continue to accumulate growing amounts of digital information. By embracing data science philosophies and tools, companies around the world should be be able to acquire more in-depth insight into the steps they need to take to stay competitive and innovative.

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