Business Analytics vs. Business Intelligence – What is the difference between the concepts of Business Intelligence and Business Analytics? What are the classic areas of application for both concepts? The terms “business analytics” and “business intelligence” have become widespread in recent years because executives want more and more insight into the processes and operational procedures of their company.

The term “analytics” comes from Greek and means “work out analytically”, meaning to calculate an answer using mathematics and not just intuition. Put simply, data analysis is concerned with finding patterns in large amounts of raw data (eg sales figures) and then using this knowledge as the basis for business decisions.

Business intelligence, on the other hand, is a process of trawling through data stores using predefined queries and reporting tools to find specific information (eg the total sales made by a product line in the past year)

The goal of business analytics is to use all available data – including transactional data, customer sentiment data, social media chatter, etc. – to make better decisions about products, services, pricing, marketing campaigns, and almost every other aspect of the business.

Business analytics can answer questions like:

• Which are our most popular products?
• How do we compare to our competitors?
• How did the last price change affect sales?
• What is the optimal product mix for our stores?

Business Intelligence, on the other hand, goes one step further by providing reports and analysis tools that can answer questions like:

• What was the revenue in each region last month?
• How many customers visited each of my branches yesterday?
• Which products should I focus on promoting this quarter to maximize profits?

Both concepts focus heavily on data analysis and the use of big data. However, business intelligence is more descriptive (reporting) while business analytics focuses more on predictive capabilities (forecasting). The goal of business intelligence is not only to gain insights from historical facts but also to use these insights as a guide for future decisions. It usually consists of two components – reporting and OLAP. Reporting includes answering ad hoc questions and preparing planned reports. OLAP stands for Online Analytical Processing and is a technology that allows users to view data from multiple dimensions (eg period, product line, region).

Business analytics has grown in importance in recent years due to the explosion in the amount of data. The goal of business intelligence is not only to gain insights from historical facts but also to use these insights for future decisions. It usually consists of two components – reporting and OLAP. Reporting includes answering ad hoc questions and preparing scheduled reports

OLAP stands for Online Analytical Processing and is a technology that allows users to view data from multiple dimensions (eg period, product line, region).

Business analytics has grown in importance in recent years due to the explosion in the amount of data available. The goal is not only to gain insights from historical facts but also to use these insights for future decisions.