Skip to content →

Big Data

Data Analytics is a system of process of understanding and presenting meaningful insight of a data set. It usually deals with large, complex, and various formatted recorded data in various disciplines. Data analytics applies statistics/mathematics, computer programming (coding), and knowledge of specific functional areas to quantify hidden information to make it useful for decision making process.

Business organizations commonly apply data analytics to summarize and report generation, structure/format data, and predict/forecast to understand business processes and to identify the areas that need further improvement. In particular, data analytics include areas of decision management, product assortment (variety) and stock-keeping (inventory) optimization, market segmentation, product mix optimization (break-even), optimum sales force or employee sizing, price optimization, predictive modeling, credit risk modeling, and credit fraud analytics. Since analytics require extensive computation, statistical algorithms and computer softwares (e.g., SAS) are used that provides the most recent methods of computing.

Data analytics can be as simple as finding duplicate records in hospital admissions or examining sales pattern and volume of products to identify the best location for distribution center. This can also be as complicated as identifying extreme outlier (statistically) in purchasing behavior for potential fraudulent in credit card activity. Analytics can use a single data table or extract data from multiple tables in multiple formats.

Data Analytics Topics

Applications of Data Analytics

Skip to toolbar