Advanced Analytics for Big Data

Big Data has emerged as one of the most challenging aspects of business data and scientific processing within the past 20 years. A major problem is that although we may be able to collect the data, we often have inadequate means for analyzing it. Kaisler, Armour, Espinosa, and Money (2013) identified some of the issues and challenges associated with using Big Data. INFORMS defines analytics as “the process of transforming data into insight for the purpose of making decisions” (2013). It involves formulating specific problems or questions; identifying, gathering and organizing the relevant data; and selecting and applying the appropriate methods, algorithms, heuristics and procedures to solve the problems or answer the questions. Analytics are quantitative and qualitative, linear and non-linear, large and small, numerical versus symbolic, and vary along other dimensions as well.