Difference Between Data Science and Business Analytics

Difference Between Data Science and Business Analytics

Data science and business analytics are related fields that serve different objectives. You use them when your company is concerned with efficiently extracting insights from data sets. Data scientists handle what the data says, while a business analyst wants to improve business results. This post will help you check if business analytics is the same as data science.

What Is the Difference Between Core Business Analytics and Data Science?

Data science focuses on future possibilities by processing data sets and obtaining projections derived by identifying trends. Therefore, the experts in data science consulting services help enterprises with risk management and long-term strategy development.

However, business analytics studies past events and the recent performance aspects affecting your company. So, data analytics services deal with already observed performance records stored in the company archives.

Now then, is business analytics the same as data science? You saw how both techniques conceptually differ and process different categories of databases. Let us learn more about the practical difference between business analytics and data science.

Scope of Data Management Methodologies

Data science firms extract every possible insight from your enterprise data using various data sources in consulting services. Therefore, their outputs differ from the final deliverables in data analytics services.

Business analytics narrows the scope to the core business problems and isolates the data trends specific to a corporate challenge. Later, you can leverage these insights to address those business issues for managerial guidance in leadership.

Data scientists use machine learning models that evolve as you input more data or update the old dataset. Business analysts do not require machine learning models in historical data analysis.

Also Read: Importance of Big Data Analytics

Skills Necessary for Professional Growth

A firm specializing in data science consulting services expects programming and statistics skills from a professional associate. Also, you must know different machine learning and modeling techniques to build a career as a data scientist.

You require an understanding of business models and corporate judgment if you want to grow as a business analyst providing data analytics services. Moreover, business analysts must be capable of capturing and structuring enterprise data.

Business analytics does not require coding skills and machine learning aptitude in all firms. Therefore, you can perform basic business analytics using statistics without much programming. The same is not valid for data science and composite data structures; you need coding to work on them.

Also Read: How to Develop and Improve Market Intelligence

Supported Data Structure Combinations

Data scientists deal with all types of data structures, i.e., structured, semi-structured, and unstructured datasets. So, many data science services integrate multimedia analysis with their consulting services.

For example, a text file with randomly arranged values lacks data structure, but processing text is more effortless. Images must support standardized metadata to be an example of semi-structured data. Still, graphics become unstructured data if their metadata is absent or incompatible.

Meanwhile, business data analytics services rely exclusively on structured data to efficiently retrieve values corresponding to a business query. In short, business analytics is not the same as data science when compared on the grounds of supporting data structures.


Business development is a challenging journey for you and your corporate stakeholders. However, using data science consulting and analytics services facilitates faster growth.

Indeed, business analytics is not the same as data science, yet some institutions think that is not the case. Therefore, we have elaborated on the difference between business analytics and data science.

You require data science to plan for tomorrow’s risks. Simultaneously, data analytics helps you understand your company’s performance in the business cycle. Additionally, high-quality data management assistance is already available for you.

A leading firm in data science consulting services, SG Analytics supports organizations through large-scale data processing infrastructure and actionable insight generation. Contact us today if you want to build impactful business growth strategies to unlock remarkable achievements.


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