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Business Intelligence vs. Data analytics: 5 Major differences

Business intelligence and data analytics are significant for business execution and management. Though used synonymously, they are different. At the same time, few similarities exist, leading to confusion.

Herein, you will know their meaning, basic concepts, and differences that help you understand them better and be devoid of any confusion.

Define Business intelligence

Business intelligence refers to the information required to enhance business decisions. It focuses on operations that drive the business towards growth, which means using some metrics that help know organizations’ operations right from the supply chain management, sales, marketing, and employee performance.

Data analytics is about refining the raw data to make meaningful insights. It focuses on the fundamental aspects of the analytical process. Moreover, data analytics incorporates presentation features common to BI, such as custom reporting and dashboards.


Business intelligence’s functionality enhances the decision-making process and helps organizations thrive. Data analytics represents, cleans, forecasts, and converts the raw data according to the business requirements.


Data analytics is performed using various data storage tools. BI tools execute business intelligence with the help of the historical information saved at data warehouses. BI tools even help implement data analytics; however, it depends on the organization’s strategy.


Business systems can be troubleshot using historical information and user requirements. Data analytics can be troubleshot through the suggested model to convert data into meaningful style.

How do business intelligence and data analytics differ? Here are the key points:

BI uses past information for present situations, while analytics helps predict the future based on different scenarios

Data analytics can predict the future. BI collects data and implements visualizations to support interpretation. This enables the stakeholders to look at past trends and decide accordingly. The process includes a model development depending on the available data and predicts things considering various scenarios.

Thereby, businesses can make informed decisions and better handle the potential risks. For instance, if you wish to know the top 10 customers of the last year, you can understand through BI. However, analytics determine who your potential customers will be based on past information; BI helps know the past, and explains why BI collects, reports, and monitors the data, while business analytics helps derive actionable insights and predict future results.

For instance, you would like to know the key performance indicators concerning production. The BI dashboard helps follow the performance versus the target for raw materials delivery from various suppliers and their rejection rate.

You could analyze that the plastics’ defect rate was high in the past month. Investigating what caused such a downfall creates improvement. Data analytics is vital for this, which helps assess the data regarding the plastic material types and data from various suppliers and arrive at the root cause.

Maybe the conclusion could be that a new component was introduced, and some technical difficulties were implemented.

BI improves efficiency, while analytics exposes new opportunities

Business intelligence and analytics choice are based on the organization’s plan. The BI solution serves well if your business model is stable and seeks to improve efficiency and make real-time decisions.

On the other end, if you wish to discover new business opportunities, analytics play vital as it helps asses organizations’ performance and the current trends so that the future can be built accordingly.

BI and Data analytics tools perform different functions

Let us know the functions of the BI and the data analytics tools. The BI tools perform the following:

  • Data reporting
  • Dashboard visualizations
  • Providing data cubes
  • Execute Ad hoc queries
  • Tracking KPIs and metrics

The analytics tools have the following functions:

  • Statistical and quantitative analysis
  • Data mining
  • Forecasting
  • Predictive modeling
  • Scenario analysis

The role of artificial Intelligence and Machine learning in advanced analytics

Data analytics has an enormous development space, while BI mostly remains unchanged. The advanced AI and ML techniques have enhanced to generate deeper insights and make predictions and recommendations. Such analytics are termed augmented analytics.  


Now, are you clear about how business intelligence and data analytics differ? Both have a unique and significant role to play in the growth of the business. Each of them is intertwined; hence one cannot exist without another.