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The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.
It can be defined as a combination of statistics, math, and computer science techniques employed to discover the patterns behind data and thus help the decision-making process. Data science generally refers to all the knowledge, techniques, and methods used for data analysis, while data analytics is the manner of analyzing massive data.
To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms. Richard is a veteran of the BI industry, having worked with analytics and data warehousing solutions from Business Objects, SAS, Teradata and SAP.
As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change.
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