Sometimes the terms business intelligence (BI) and business analytics (BA) are loosely thrown around, especially among non-IT professionals, and this can be confusing. As data management and analytics are becoming key aspects of business, let’s take a closer look at both BI and BA and highlight the difference between them from the business-user perspective.
From a high-level point of view, BI uses descriptive analytics to provide a better understanding of a business’ current operations. Meanwhile, BA usually looks forward and tries to inform future decisions.
At its core, BI is a process of analyzing data and presenting information to decision-makers. This leads to a better understanding of a present situation and events that led to the situation.
Today BI is inherently association with modern IT, however, the idea and process themselves have existed for a while. At the dawn of industrial manufacturing, for example, engineers began to gather, formalize, manage, and analyze production techniques to find efficiencies, which could improve production. Obviously, their tools weren’t the same, in most cases they used pen and paper; but the idea behind the process was the same (or at least very similar).
Nevertheless, BI as we know it, came into relevance with the widespread development of computers and modern databases, which could quickly calculate and store large numbers for business needs.
As a process, BI relies on data and descriptive analytics techniques to paint a present picture and provide insights. Descriptive analytics provides a look into past numbers and can answer why, where, and how a company failed or succeeded. This is done in the form of capturing data, storing it in databases, finding insights, publishing reports and dashboards.
As we said earlier, BI helps to understand what was done right or wrong to this point, and this is where BI and BA differ. Instead of focusing on historical data, BA focuses more on providing actionable insights for decision-makers and predicting future trends.
To do these things, BA, like BI, also uses historical data points; however, instead of descriptive analytics BA relies on predictive analytics.
The BI and BA processes are closely connected, as BA takes BI and attempts to provide insights on future success or failure. Using predictive analytics BA finds correlations in existing information and builds models for future planning. The predictive nature of BA differs from BI in the tools being used. BA focuses on complex statistical models and predictive modeling; meanwhile, BI uses simpler descriptive statistical toolbox.
As both BI and BA rely on the same data, many businesses traditionally start with using BI and then get into analytics. BI can show a full picture and point out areas where one could dig deeper. After that, BA tools go to work to uncover more insightful information and provide interesting predictions.