by Angela Guess
Sandeep Raut gives a useful definition of business analytics in a recent article: “Business Analytics is the use of statistical tools & technologies to: (1) Find patterns in your data for further analysis e.g. product association, (2) Find out outliers from the huge data points e.g. fraud detection, (3) Identify relationships within the key data variables for further prediction e.g. next likely purchase from the Customer, (4) Provide insights as to what will happen next e.g. which of the Customers are leaving us, (5) Gain the competitive advantage.”
Raut goes on to contrast business analytics and business intelligence, noting that intelligence “reports on what happened in the past or what is happening now” whereas analytics “investigate why it happened and predict what may happen in the future.” Business intelligence, according to Raut, is achieved through “Basic querying and reporting; OLAP cubes, slice and dice, drill-down; [and] interactive display options – dashboards, scorecards, charts, graphs, alerts.” Business analytics, on the other hand, is achieved through “Applying statistical and mathematical techniques; identifying relationships between key data variables; [and] revealing hidden patterns in data.”
Raut goes on to discuss the six major components of any analytics solution: data mining, text mining, forecasting, predictive analytics, optimization, and visualization. For more on each of the components, see the full article.