Business Intelligence vs Data Science
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Jul 8, 2024
The terms "business intelligence" and "data science" can be difficult to dissociate due to their many similarities. However, they are indeed two distinct disciplines.
So, what is the difference between data science and business intelligence?
This is what we will see right away, thanks to this article, the confusion between BI and data science will be a distant memory!
What is Business Intelligence?
If you have read our article Business Intelligence: Definition and Objectives you already know perfectly what BI is. Nonetheless, here is a brief reminder.
Business Intelligence is a process that encompasses various tools, methods, and applications that allow analyzing the data of a company or a multi-site group through dashboards, reporting, and other reports.
BI provides an overview of a company's management and its performance, thanks to data that has been previously collected, centralized, and organized. This data is then transformed into relevant information, based on the past and present of the company, which allows decision-makers to make better decisions for their activities.
What is data science?
Data science is a discipline newer than BI. It relies on data analysis but also and especially on the exploitation of this data by the company.
Just like BI, Data Science has become essential for effectively managing a company and discovering opportunities for improving products and services.
More broadly, data science enables the implementation of new strategies related to the future of the company.
To achieve this, Data Science will rely on profiling segmentation, predictive analysis, and more generally, on Artificial Intelligence to accurately predict future behaviors.

Data science is an innovative discipline that encompasses not only mathematics and statistics, but also computer programming and AI, in order to establish algorithms capable of anticipating trends and thus creating the best possible strategies for the company.
Similarities between Business Intelligence and Data Science
The main common point between BI and Data Science is their overall objective. Both concepts aim to collect, analyze, and exploit data to aid in better decision-making, even if data science is more complex than decision-making informatics.
Moreover, business intelligence and data science are complementary. Analysts or business intelligence consultants can prepare relevant information that can then be more easily utilized in the context of data science.
Beyond their complementarity, data science can thus be perceived as an evolution, a natural extension of business intelligence.
In any case, the use of these two disciplines together facilitates processes and the good management of the company. Thus, experts from these two disciplines can work together on the same project to achieve better results.
Differences between Data Science and Business Intelligence
The major difference between these two disciplines lies in the fact that Business Intelligence is based on the analysis of a company's historical and current data to derive trends, while Data Science uses artificial intelligence and algorithms to predict future behaviors. Data science thus aims to anticipate, to determine the most "probable" future in order to implement the most suitable actions.
This is called predictive analysis. It consists of validating or invalidating hypotheses using data science.
The approach here is less "structured" than for Business Intelligence, which relies on a more descriptive analysis.

Also, the tools used differ according to the discipline. BI mainly relies on software, while data science relies more on programming.
Data science is more precise, more advanced in data analysis, process optimization, and improving operational performance of the company.
It is also more complex; dedicated analysts must possess numerous skills. Moreover, some BI tools are increasingly making data accessible to non-specialized users.
It is not a matter of choosing between one discipline or the other but rather of using the solution best suited to the insights you wish to obtain. Additionally, the challenge for decision-makers, with all these tools and applications available, is not to get lost in a flood of information but to maintain a clear visibility on the opportunities generated.
In summary:
Business Intelligence (BI) and Data Science are two distinct disciplines that can be difficult to differentiate due to their similarities. BI is a process that uses tools, methods, and applications to analyze a company's data through dashboards and reports, in order to provide relevant information for decision-making. Data Science, on the other hand, is a newer discipline that focuses on analyzing and exploiting data by the company, using algorithms and Artificial Intelligence to predict future behaviors. Although both disciplines have the overall goal of collecting, analyzing, and exploiting data to aid in decision-making, Data Science is more complex and focuses on predictive analysis, while BI is based on the analysis of historical and current data. The two disciplines are complementary and can be used together to improve company management.
F.A.Q :
What is the difference between Business Intelligence (BI) and Data Science?
While both disciplines focus on data analysis to aid in decision-making, BI relies on the analysis of historical and current data to identify trends, whereas Data Science uses artificial intelligence and algorithms to predict future behaviors.
Is Data Science more complex than BI?
Yes, Data Science is more complex than BI; dedicated analysts must have many skills in programming, statistics, and machine learning.
How to choose between BI and Data Science?
It is not about choosing between one discipline or the other, but rather about using the solution best suited to the information you wish to obtain. The challenge for decision-makers is not to get lost in a flood of information but to maintain a clear visibility on the opportunities generated.