Business Analytics- The Next Big Thing
Business Analytics is one sector which has been growing rapidly with organizations such as Flipkart, Amazon, Walmart, Facebook recruiting various talents across B-Schools offering specialized Business Analytics course. Most organizations used to outsource major analytics work to pure analytics firm but today, in-house analytics teams are preferred. B-Schools such as SOIL Institute of Management have realized the growing awareness about business analytics and buzz words like Data Mining, Big Data, Text analysis are captured by courses offered in SOIL.
Why Business Analytics?
Business Analytics helps to decode the Why, What and How questions from any organization. The huge amount of data available to organizations help to decode why part. The what part is the ability to work a huge amount of data, analyze and break it down into critical insights.
Business Analytics requires to define the current state, desired state, identify the gap between the desired and current state, generate and evaluate hypothesis and last but not least, storyboarding and visualization. Above processes are carried out for which different form of analytics are used such as Descriptive, Diagnostic/ Inquisitive, Predictive and Prescriptive analytics.
- Descriptive gives an overview of what has occurred in business and is presented in the form of old data and takes the form of reports, flowcharts, etc.
- Diagnostic/Inquisitive helps in understanding why something has happened until a particular time which involves drilling into the data through traditional methods such as regression, factor analysis, etc.
- Predictive Analytics part deals with what can happen in the future and involves a high analytics bent of mind which is used to predict the future of using data modeling and forecasting methods.
- Prescriptive Analytics part deals with what to do which is meant to tackle the predictions made and take the business to the top.
Proprietary software such as SAS and IBM SPSS. But most widely used software is R due to the ease of availability. R and SAS are mostly used for Predictive Analysis, SQL and Teradata is suitable for smaller data pulls.