Business Intelligence Vs Data Analytics: What’s the Difference?

What is Business Intelligence Vs Data Analytics?

In today’s technology-driven business world, big data is influencing and empowering the decision-making process everywhere.

Whether higher education, government agencies, or large business empires, data rules everywhere. Data insights help organizations expand their reach, boost sales, operate more efficiently, and launch new products or services.

For data to make sense and be more competitive, organizations need to apply both business intelligence and data analytics. However, there is often confusion about these two areas, which can seem interchangeable and related.

Business intelligence and data analytics involve working and analyzing data for insights that can help accelerate sales and boost business growth. But what are the main differences between the two?

We can say that business intelligence deals with complex business strategies and technologies that can help in analyzing complex data to gain decision-making business insights to grow one’s business.

On the other hand, data analytics is used to convert the raw, unstructured data into a meaningful data format. This structured data can then be utilized to derive meaningful data insights and support the decision-making process. 

This article will examine the differences and similarities between Power BI and Data Analytics and compare the roles and responsibilities that can guide you to decide which path is right.

Big Data - All aspects that constitute it
Big Data

What is Business Intelligence?

Business intelligence is a broader term and can be defined as collecting, analyzing, integrating, and organizing raw data into a structured format to deliver insights for making better future decisions. Simply put, “BI is getting the right information to the right people at the right time.”

In short, “Business Intelligence” enables the business to make intelligent fact-based decisions by transforming raw data into useful insights.

The 6 key aspects of Business Intelligence
Business Intelligence

What is Data Analytics?

Data analytics is the process of collecting, segregating, and analyzing data to discover useful information and other helpful business insights for decision-making.

It helps to determine which data is relevant and can be analyzed to drive better business decisions in the future. Many commercial, as well as open-source, tools, are available for data analytics in business as well as analytical organizations.

A visualization of data analytics, representing it with different graphs, charts, and diagrams.
Data Analytics

Working With Data Analytics

Businesses need data analytics basically for:

  1. Analyzing the data to gain insights for better decision-making.
  2. The data insights gained, in turn, can help to perform market analysis and improve the business strategy.
  3. Data analytics can help businesses understand customer need trends and stay relevant to customer needs.

Differences Between Business Intelligence and Data Analytics

The distinctions between Power BI and data analytics are subtle and make things more confusing. Keeping in mind the current business trends, we can say that both these terms can be used interchangeably.

Today’s business intelligence tools are equipped with inbuilt data analytics options. It ultimately depends upon the end-user which one to choose based on their business needs as both BI and data analytics play a crucial role in business growth. Necessary research is being carried out by the business on BI and data analytics to serve their purpose efficiently. 

Business Intelligence was designed so that these ever-increasing amounts of data can be arranged and analyzed. Similarly, data analytics is designed to help organize and streamline growing amounts of data. Every day, loads of data are generated, which has necessitated developing newer and better technologies to collect, organize, and analyze valuable business insights.

Key Differences Between BI and Data Analytics

All of these processes leverage data to improve your business, but let’s push a little further to understand the differences between each.

Business IntelligenceData Analytics
Prime PurposeSupport decision-makingConvert and cleanse raw data
PerspectiveLooking BackwardLooking Forward
Types of QuestionsWhat happened?What will happen?
DataWarehoused, structuredReal-time, mostly unstructured
Typical UsersCEOs, CFOs, CIOsData scientists, IT Pros
ScopeUnlimitedSpecific issue/question
KPI Reports
Data Mining &Text MiningSimulations
Quantitative analysis
Differences Between BI and Data Analytics

Similarities Between Business Intelligence and Data Analytics

It is crucial to know the differences between Power BI and data analytics, but knowing their similarities is also important. This can help businesses understand how each one of them can similarly benefit their business.

Both these fields can “interpret data” and usually engage data experts who translate or transform data-enriched results in friendly insights or competitive intelligence.

Additionally, both Power BI and data analytics follow similar data analysis processes, i.e., similar ways of collecting data and analyzing it into useful insights.

Lastly, both of these terms also engage in data reporting. This means that the data is analyzed and visualized to make it easier to understand the insights to understand and act upon.

Both of them can also identify areas where businesses need to improve and operate at their peak performance.

Similarities Between BI and Data Analytics: Summary

By now, you must have understood the similarities between these two functionals. To summarize, we can say:

  • Both Power BI and Data Analytics focus on data to provide desired outcomes, which in business can be customer management, profit details, market insights, etc. 
  • Both of them can “interpret data” and usually utilize the knowledge of technical experts who translate or transform data-enriched results in friendly data insights for competitive intelligence.
  • Both Power BI and Data Analytics offer reliable decision-support systems to business organizations and their employees who are experts in their respective fields of work and expect reliable help and support from data experts to make data-driven decisions.


Now we know the overall picture of the similarities and differences between these two functionalities. But it is to be noted that the uses of these functionalities may vary across different business formats.

Does this post answer all the questions you had in mind? No, right? 

No matter how we define or explain it, people will always use these terms interchangeably. So, it doesn’t matter if someone says, “Data analytics is how you get to business intelligence” or “Business intelligence encompasses data analytics”? 

The conclusive point of both processes is to analyze data and create reports to improve decision-making. 

Whatever may be the case, contact Loginworks and get in touch with our experts now with your Power BI and Data Analytics requirements.

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