If you’re in the managerial or strategy space, chances are, you might have heard of the terms business intelligence and business analytics. Sometimes, people use them interchangeably, which adds to the confusion because there certainly are important differences between them. However, what do these terms really mean and what are the essential differences between them? Read on to know that and more!
Business Intelligence is All About Data
Business Intelligence is when a manager uses data to drive operational frameworks in the company. It is common for the management of any company across industries to collect data from multiple sources and use it to improve workflows, efficiency, and quality.
A number of tools can be used to drive business intelligence: from simple spreadsheets to complex data mining software.
Business Analytics is All About Predictions
Like business intelligence, business analytics too harnesses data from across sources, but there’s a key difference in how this data is used. Business analytics puts more emphasis on statistical techniques and using data to make predictions and craft strategies for the future.
Business analytics is thus future-oriented. Oftentimes, business analytics relies on complex tools and leverages experts with skill sets ranging from computer data scientists to data mining.
The Difference Lies in Past vs Future
As you might have noticed already, the difference between business intelligence and business analytics lies in the time periods they are invested in.
While business intelligence would give a manager an idea of their processes at a point in time in the past, business analytics would help them create personas for their future processes or customers, for instance.
There’s a significant overlap between both fields though, and experts differ in their opinions. Business intelligence is often used to get key insights about business which then form the foundation for further study and research that business analytics undertakes.
Both paradigms use data at their core but the approaches differ.
Description vs Prediction: Other Differences between Business Intelligence and Business Analytics
Business intelligence will often help brands create strategies and decisions for current challenges and problems at hand. On the other hand, business analytics will create strategies that deal with future operations.
Business Intelligence is often descriptive and business analytics predictive. Business Intelligence (BI) typically deals with dashboards and visual aids to understand data and use it to drive decisions. Data is examined in the form of reports and tables customized for user personas: managers, analysts, leaders, etc.
Business Analytics (BA), on the other hand, has a complex toolset, including software applications and tools. While BI deals with big data, BA harnesses that big data and makes sense of it for key decisions that will shape the future of a company.
Similarities between BI and BA
There are a lot of commonalities between Business Intelligence and Business Analytics. Both rely on harnessing data. Similarly, both will analyze large data sets with different aims. However, analysis is an integral part of both approaches.
The source of data is diverse— data gathered from surveys, organizational data, data from across customer touchpoints: everything goes into the data pool. A variety of statistical and data modeling tools are used. Common BI and BA solutions include SAP Analytics, SAS Analytics, Zoho Analytics, and others.
Wrap Up
Both business intelligence and business analytics are terms used interchangeably in business parlance but they actually differ considerably. While business intelligence is more concerned with harnessing data to understand past situations, business analytics concerns itself with using data to make predictions for the future.
While some experts believe Business Analytics forms a part of the broader Business Intelligence approach, others believe it’s the other way round. The ideal approach, in the end, is to use both BI and BA to the best effect. The aggregation of data is common to both frameworks and so is analysis.
Companies can bolster productivity, improve efficiency, and cut down costs with the use of an amalgamated strategy that blends the power of business intelligence and business analytics. The result will be an approach that gathers data and converts it into digestible and actionable insights. This will help brands see a bird’s eye view of their businesses and see where they’re heading.
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