The Difference Between Data Science and Business Intelligence

Companies around the world use various techniques to analyze their data and gain a competitive advantage in the market. In the 21st century when the world is drowning in data, it becomes really important for companies to store and analyze it so that they can make sense out of it. They combine and transform that data to find hidden patterns or establish a relationship between different variables, which would otherwise be very difficult. It’s done using Data Science techniques and models that equip data scientists with the right tools to perform such operations. 

However, the data transformed by a data scientist is hard to understand by other users and non-technical decision-makers. For this reason, companies’ Business Intelligence tools such as Power BI, Tableau, etc enable them to equate the data from various sources, visualize, and share the reports with others to track the progress of different departments. It truly brings the leaders and decision-makers together on a single platform. 

Although Business Intelligence and Data Science are two closely related disciplines, we must understand the difference between them to accurately forecast future trends. As a data science enthusiast, you can learn the nuances of the technology. You can do so by taking some Data Science Courses and getting hands-on experience on various projects. 

What is Business Intelligence?

Business Intelligence is a collection of various technologies, processes, and tools used to perform a descriptive analysis of the raw data and make informed decisions. This set of tools enables the business users to collect, govern, and transform the data to get a better understanding of the customers, product performance, and the current state of the market. 

Business Analytics allows a user to create visualizations based on the requirements and share them with others in the form of dashboards and reports. It connects live data sources with the visualizations to give a streamlined view of the current market situation and give businesses a strategic advantage in the market. 

What is Data Science?

Data Science is an interdisciplinary field that allows you to extract valuable information from the data using various algorithms, processes, and scientific methods. It’s a combination of statistics, mathematical functions, algorithms, Machine Learning models, and AI processes that help you to find hidden patterns from the data and predict future trends. By integrating cloud computing technology, you can deal with both structured and unstructured data and accurately predict the impact of decisions on the market. 

Difference between Business Intelligence and Real Data Science

Let’s understand the difference between these two technologies based on the skills, data sources, and area of expertise:

Area of Expertise

Data Science has expertise in data analysis, predictive modeling, and studying the hidden patterns from various data sources. These models can be deployed on both structured and unstructured data to establish the relationship between different data variables and improve business performance. 

In contrast, Business Intelligence allows you to create visually interactive reports and dashboards to reveal the key performance metrics and other trends. 


To upscale your career in Data Science, you should be proficient in various programming languages and tools like Python, SAS, R, SQL, Hadoop, Spark, data structures, etc. Business Intelligence skills include problem-solving, MySQL, knowledge of Tableau, Python libraries, ETL(Extract, transform, load) capabilities, cloud computing, etc. However, professionals in both technologies should have excellent communication and presentation skills, teamwork, Machine learning, and documentation skills. 

Business Intelligence vs Data Science

Below are the key differences between Business Intelligence and Data Science:

Business Intelligence Data Science
It’s the set of techniques and processes used by various businesses for data analysis and visualization.  Branch of Computer science that utilizes statistical and mathematical models to find the hidden patterns in different datasets. 
BI focuses on past and present-day trends. Data Science is used to predict future events based on the available data.
Mostly used for structured data. Used to analyze both structured and unstructured data.
Business Intelligence uses analytical methods to transform raw data into actionable insights. Data Science uses scientific methods to analyze the data. 
Used by Business users to analyze and visualize the data. Mainly used by data scientists.
Less flexible as the data sources should be pre-planned. Data sources can be added or removed as per the requirements, thus providing more flexibility. 



Hope you got all the information that establishes a difference between these two relevant technologies used for data analytics and visualization. While Business Intelligence deals with business connectivity, project management, data visualization, report generation, and resolving strategies. Data Science is associated with processing and transforming the data, building predictive models, discovering hidden patterns, and predicting future events.