|Data Analytics: Refers to qualitative and quantitative techniques and processes used to enhance productivity and organizational gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements.|
Data analytics is an evolving and multidisciplinary area of study in which there are as many different definitions as there are definitions. Despite these differences, data analytics generally seeks to support the decision making through:
(a) Application of organizational understanding to identify the issues and outcomes of import to decision makers
(b) Process of acquiring and analyzing data that leads to information based insight.
Analytical Applications and Disciplinary Areas:
Organizational / Business Analytics: Application of analytical techniques to determine and understand the effectiveness of organizational or business functions. Analytics can be either focused on internal or external processes. Different specializations exist, encompassing most major aspects of organizational action, including risk analysis, market analysis, and supply chain analysis.
Data Analytics: Organizational Value vs. Difficulty
Descriptive Analytics: Describes or summarizes raw data and makes it something that is interpretable by humans. It uses descriptive statistics to understand at an aggregate level what is going in an organization and to summarize and describe different aspects of that organization.