Analytics: Key to Go from Generating Big Data to Deriving Business Value

The potential to extract actionable insights from Big Data has gained increased attention of researchers in academia as well as several industrial sectors. The field has become interesting and problems look even more exciting to solve ever since organizations have been trying to tame large volumes of complex and fast arriving Big Data streams through newer computing paradigms. However, extracting meaningful and actionable information from Big Data is a challenging and daunting task. The ability to generate value from large volumes of data is an art which combined with analytical skills needs to be mastered in order to gain competitive advantage in business. The ability of organizations to leverage the emerging technologies and integrate Big Data into their enterprise architectures effectively depends on the maturity level of the technology and business teams, capabilities they develop as well as the strategies they adopt. In this paper, through selected use cases, we demonstrate how statistical analyses, machine learning algorithms, optimization and text mining algorithms can be applied to extract meaningful insights from the data available through social media, online commerce, telecommunication industry, smart utility meters and used for variety of business benefits, including improving security. The nature of applied analytical techniques largely depends on the underlying nature of the problem so a one-size-fits-all solution hardly exists. Deriving information from Big Data is also subject to challenges associated with data security and privacy. These and other challenges are discussed in context of the selected problems to illustrate the potential of Big Data analytics.