In the business world, Big Data and Analytics represent the process for managing, discovering and analyzing meaningful patterns in data sets; which often are so large and complex that traditional databases and applications are insufficient to deal with them. Analytics rely on the use of effectively structured information, and the application of algorithms and statistics to determine and define trends, problems, and opportunities.
In the new Digital Economy, enterprises now rely Big Data and Analytics to analyze, describe, predict, and improve business performance; to a point where the overall success or survival of many companies depend on their strategy for using Big Data and Analytics.
While individuals with a technical background—such as CTOs, CDOs, and Data Managers— understand the technological and operational benefits of Big Data and Analytics, many of the non-technical business managers and professionals have not been able to economically forecast, and measure the benefits from investments in Big Data and Analytics.
Nonetheless, while the business outcomes of the early types Analytics, which appeared decades ago, were difficult to predict, Analytics have evolved; and these days the various types of are Analytics are becoming easier to forecast and measure. Today we can find informative-type analytics, predictive analytics, prescriptive analytics, and automation analytics with the Internet-of-Things.
The uncertainty in the effects and benefits of Analytics has been decreasing, and the economic benefits of Analytics solutions are becoming easier to anticipate, measure, and economically quantify.
To learn more about “Tangibilizing” the intangible benefits of Big Data, Analytics and IoT, go to ->