Business Analytics vs Business Intelligence

business analytics vs business intelligence

If you work in the field of data analysis, you’ve probably heard the terms “business analytics” and “business intelligence” used interchangeably. However, although they are similar, there are some important differences between the two concepts. In this blog post, we’ll take a closer look at business analytics and business intelligence and explore the key ways in which they differ.

What is Business Analytics?

Business analytics is a set of analytical methods and tools / technologies for analyzing and solving business problems by gathering, analyzing, understanding, discovering and communicating significant patterns in the data. In other words, it is a process or set of methods / steps for exploring and uncovering significant patterns from data with the goal of of improving business performance. Business analytics typically makes use of some of the following tools to generate and communicate insights from data.

  • Reports (excel-based reports) primarily for understanding past, present and future state of business. They mostly form a part of descriptive analytics.
  • Dashboards (Tableau, Qliksense, etc) primarily for visualizing the past, present and future state of business. They mostly form part of descriptive analytics.
  • Predictive analytics (AI / machine learning algorithms) to assess / evaluate future state of business

What is Business Intelligence?

Business intelligence (BI) is a process for extracting and communicating intelligence / insights from data that can be used to make better business decisions. In simple words, BI is the practice of gathering data from various sources inside and outside of an organization to identify patterns and trends that can be used to make better business decisions.

Business intelligence can be understood as the subset of business analytics. The “intelligence” keyword represents insights which get discovered from the dataset. 

The following are some of the popular BI tools which can be used to extract intelligence from the dataset:

  • Tableau
  • QlikView
  • Microsoft Power BI
  • Google sheets
  • Microsoft Excel
  • SAP Lumira
  • SAP Crystal Reports
  • IBM SPSS
  • Spotfire
  • SAP BusinessObjects

The tools for BI can also be used as tools for business analytics. 

Key Differences & Similarities: Business Analytics & Business Intelligence

The following are some of the key differences between business analytics and business intelligence:

  • Business analytics can be represented as a set of methods and tools for solving business problems by discovering patterns from data. Business intelligence can said to be a set of methods and tools which can be used to extract insights / intelligence from the data.
  • Business intelligence can be said as subset of business analytics.
  • A BI developer would most likely work with dashboards, reports etc while a business analytics personnel would work in analyzing business problems and solving them by leveraging data / insights using analytical tools & techniques. 
  • Tools used for BI can also be used for business analytics.

Conclusion

As you can see, although business analytics and business intelligence are similar, there are some important differences between the two concepts. When choosing a solution for your organization, it’s important to understand these differences so that you can select the right tool for your needs.

Ajitesh Kumar
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Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking
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