Chapter 1

Business Analytics: A Definition

Before we define the guidelines that establish best practice, it’s important to spend a bit of time defining business analytics and why it’s different from pure analytics or advanced analytics.1


The cornerstone of business analytics is pure analytics. Although it is a very broad definition, analytics can be considered any data-driven process that provides insight. It may report on historical information or it may provide predictions about future events; the end goal of analytics is to add value through insight and turn data into information.

Common examples of analytics include:

  • Reporting: The summarization of historical data
  • Trending: The identification of underlying patterns in time-series data
  • Segmentation: The identification of similarities within data
  • Predictive modeling: The prediction of future events using historical data

Each of these use cases has a number of common characteristics:

  • They are based on data (as opposed to opinion).
  • They apply various mathematical techniques to transform and summarize raw data.
  • They add value to the original data and transform it into knowledge.

Activities such as business intelligence, reporting, and performance management tend to focus on what happened—that is, they analyze and present historical information.

Advanced analytics, on the other hand, aims to understand why things are happening and predict what will happen. The distinguishing characteristic between ...

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