Business analytics is “the use of math and statistics to derive meaning from data in order to make better business decisions.”, according to the Harvard Business Review’s video. The video says that there are three types of analytics: descriptive, predictive and prescriptive. It does not have the fourth one: diagnostic. Descriptive analytics include reports, dashboards, scorecards and alerts. They tell you what happened in the past, but not why it happened or what might change in the future. Compare the term business intelligence. Diagnostic analytics attempts to answer why it happened. Predictive analytics uses past data to model possible future outcomes. How will customers respond and what will our sales be? Prescriptive analytics are the most useful. They use optimization and A/B testing to make recommendations to decision-makers. This could be a marketing mix decision such as setting the price or deciding where and when to advertise.
In an article, Harvard Business School Online’s Business Insights Blog says: “There are four key types of business analytics: descriptive, predictive, diagnostic, and prescriptive. Descriptive analytics is the interpretation of historical data to identify trends and patterns, while predictive analytics centers on taking that information and using it to forecast future outcomes. Diagnostic analytics can be used to identify the root cause of a problem. In the case of prescriptive analytics, testing and other techniques are employed to determine which outcome will yield the best result in a given scenario.”
Let’s compare the definition of Data Analytics. It’s really the same thing except that Business Analytics focuses on business decisions, whereas Data Analytics includes all industries and organizations, including government organizations.
Types of Data Analytics
The goal of data analytics is to derive insight from data. According to the book Fundamentals of Data Engineering by Joe Reis and Matt Housley (O’Reilly) on page 348, there are three types of analytics: business, operational and embedded.
- Business Analytics – historical and current data is used to make business decisions
- Operational Analytics – use data to take immediate action, real-time monitoring, factory, assembly, defects
- Embedded Analytics – external-facing, end users consume data, dashboards, smart thermostats
The other consumer of data is the machine learning algorithms built by data scientists.