Decoding Business Analytics vs. Business Intelligence

Why did it happen?

Will it happen again?

What insight does it offer?

What happens if changes are made?

These are questions typically asked during the process of Business Analytics.  Business Analytics uses a pre-established method to find patterns and relationships, to gain insights, to forecast future outcomes and conduct experiments to test decisions.

What happened?

When did it happen?

Who or what factors influenced the same?

How many outcomes are possible?

This forms the essence of Business Intelligence practice, although it is an umbrella term that extends to applications and technologies for data sourcing, storage, online analytical processing (OLAP)and forecasting  to respond to a decision support system (DSS) that supports query and reporting

 BI table

BA and BI

A typical scenario that illustrates the difference:

Let’s say I work for the State Department of Disaster Management, where my work includes collecting data during a natural disaster like cyclone to improve response time and disaster preparedness.

  • Querying BI reports will tell me the details of impacts of last few cyclones – Which regions are most affected, which regions received delayed response, and so on. This examination of past events is descriptive analytics. This forms the core of Business Intelligence.
  • I also make use of the BI tools our department has invested in, to visualise any correlation between say, impact of cyclone and delay in response, or distance from district offices and delay in response – to determine correlations. This is diagnostic analytics.
  • I use a data scientist or analyst to create a model that uses such historical trends in data, other variables like decisions made and their impacts, good / bad; factors determining response time, time taken to reach disaster zone, and so on – to ‘make predictive models’ that form the roadmap for future disaster management. This is data analytics or predictive analytics.
  • Once I have tried and tested such predictive model, I will use the outcomes to make changes and design a suitable prescriptive model for tackling future disaster response.  This is prescriptive analytics.



Summing up,  at the end of the day, the terms Business Analytics and Business Intelligence are complementary and often used interchangeably, depending upon how an organisation implements it.

As Timo Elliot puts it,

… nobody important cares what this stuff is called. If you’re in charge of a project, what matters is working out the best way to leverage the information opportunity in your organization, and putting in place appropriate technology to meet that business need — and you can call that process whatever you like: it won’t make any difference…

Bottom line: So when you come across a job posting in the domain of Business Analytics / Business Intelligence, do not get fazed. Check out the company profile, experience requirements, technologies in use and draw your own inferences on what they are looking at. Good luck!

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