Business Intelligence vs Data Science

The terms "business intelligence" and "data science" can be difficult to separate due to their numerous 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 just a distant memory!‍

What is Business Intelligence?

If you have read our article Business intelligence: definition and objectives , you already know perfectly well what BI is. Nevertheless, here is a brief reminder.

Business Intelligence is a process that encompasses several tools, methods, and applications that allow for the analysis of a company’s data or a multi-site group through dashboards, reporting, and other reports.
BI provides an overview of the management of a company 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 enables decision-makers to make better decisions for their activity.

‍What is data science?

Data science is a more recent discipline than BI. It relies on the analysis of data but also, and above all, on its exploitation by the company.
Like BI, Data Science is becoming essential for effectively managing a business and discovering opportunities for improving products and services.
More broadly, data science enables the development of new strategies related to the future of the company.

To achieve this, Data Science will rely on profile segmentation, predictive analysis, and more generally, on Artificial Intelligence to be able to predict future behaviors.

Data science is an innovative discipline that encompasses both mathematics and statistics, as well as computer programming and AI, in order to implement algorithms capable of anticipating trends and thus creating the best possible strategies for the company.

‍Similarities between Business Intelligence and Data Science

The main similarity 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 though data science is more complex than decision-making informatics.

Furthermore, business intelligence and data science are complementary. Analysts or business intelligence consultants can prepare relevant information that can then be more easily exploited in the context of data science.
Beyond their complementarity, data science can thus be viewed as an evolution, a natural extension of business intelligence.
In any case, using these two disciplines together facilitates processes and effective management of the company. Thus, experts from both 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 historical and current data of the company to identify trends, while Data Science uses artificial intelligence and algorithms to predict future behaviors. Data science therefore aims to anticipate, to determine the most "probable" future to implement the most suitable actions.

This is referred to as predictive analysis. It involves validating or invalidating hypotheses through data science.
The approach here is less “structured” than for Business Intelligence, which relies on a more descriptive analysis. 

Also, the tools used differ depending on the discipline. BI relies mainly on software, while data science is more based on programming. 

Data science is more precise, more advanced in data analysis, process optimization, and improving the operational performance of the company. 

It is also more complex, with dedicated analysts needing a wide range of skills. Furthermore, some BI tools are increasingly making data accessible to non-experts. 

It is not about choosing one discipline over the other, but rather using the most appropriate solution for the insights you want to obtain. Moreover, the challenge for decision-makers, with all these tools and applications at their disposal, is not to get lost in a flood of information but to maintain 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 to provide relevant information for decision-making. Data Science, on the other hand, is a more recent discipline that focuses on the analysis and exploitation of data by the company, using algorithms and Artificial Intelligence to predict future behaviors. Although both disciplines share the overarching goal of collecting, analyzing, and utilizing data to assist 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 enhance company management.

F.A.Q :

What is the difference between Business Intelligence (BI) and Data Science?

Although both disciplines focus on data analysis to assist in decision-making, BI relies on analyzing historical and current data to identify trends, while 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 a wide range of skills in programming, statistics, and machine learning.

How to choose between BI and Data Science?

It is not about choosing one discipline over the other, but rather using the most appropriate solution for the insights you want to obtain. The challenge for decision-makers is not to get lost in a flood of information but to maintain clear visibility on the opportunities generated.

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