Business Analytics is a topic that is often confused with Big Data. While the analysis of Big Data is related to the continuous analysis of business information through an analytical process, they are related concepts rather than exactly the same thing.
There are various kinds of analytics to start with:
Descriptive Analytics: how to gain insight from historical data, creating reports and scorecards that give a better vision of some existing data.
Predictive analytics: modeling through the use of predictive models and machine learning – allowing the system to learn what might happen next based on the data that is being studied usually in real-time.
Prescriptive analytics: taking a large data-set and attempting to create decisions, choosing possible paths, simulating what might happen if certain decisions are taken.
Decisive analytics: this supports human decision-making with very visual analytic information that helps the user.
So the field of Business Analytics is more related to the process of taking data and either modeling outcomes or predicting what may happen next, rather than just attempting to spot trends in a large data set.
Business Analytics is really a tool that can support executives to make better decisions by supporting their decisions with data, rather than just estimates or guesses. By using actual data from the business and modeling potential outcomes based on decisions that could be taken, the data can help to support the direction a business leader should take.
This type of process has existed for a long time, but it has been the creation of vast pools of business data – the move towards a Big Data environment – that has really stimulated the need for improved Business Analytics. The increased amount of data has provided more information that can be analysed and yet has also made it more difficult to reach a conclusion on the right decisions – without better analysis.