Business analytics and data analytics incorporate working with data, extracting the insights, and using the extracted data to improve business performance and growth. So, what are the basic differences between business analytics and data analytics?

The term business analytics tends to a package of applications, tools and skills that enables the business to analyze and enhance the productivity of business operations such as sales, customer service, IT or marketing. Business analytics come in the role when we talk about larger business implications of data and the related outcomes.

Data analytics incorporates combining big datasets to showcase trends and patterns, support your business decisions and draw conclusions about actions with data-based insights. Data analysis helps businesses find out the answer for questions like “What is the impact of geolocation or seasonal or festive factors on customer’s choices?

Data analytics covers lots of practices, approaches and methods. Additionally, it tends to data mining, data modelling, big data analysis and data science.

Every second 70,000 search queries get placed on Google, and more than 1.2 trillion searches get placed every year.

Business analytics is used to find out the issues and solutions; however; there is less of a role of deep data analysis. Professionals of business analytics define and communicate with the concerned people and help them know the implications of business data.

Whereas, data analytics professionals collect, clean and transform data into valuable information. They apply state-of-art technologies to extract useful and valuable information and provide better solutions.

According to reports, “the data analytics sector in India alone is predicted to achieve 7x growth to reach $16 billion by 2025.”

A deep insight into business analytics

The repetitive exploration of a company’s data with the motive of implementing statistical analysis techniques is termed as business analytics. It is used to determine the specific data that can help businesses drive growth and financial performance.

Organizations using analytical data approaches always consider big data as a useful asset that is profitable in terms of support strategies and business planning. Business analytics enables businesses to maximize their value with profitable insights of data.

The three types of business analytics are:

  1. Descriptive,
  2. Predictive,
  3. Prescriptive.

All three types of BA (Business Analytics) are applied in different stages and help you solve and find out the best answers for queries an organization may have.

Descriptive Analytics enables businesses to determine the answer for “What happened?” As the question describes, such analytics helps you find out the historical data and insights to plan for future outcomes.

Whether there are lots of tools, dashboards and other ways available to find out the insights of data, professionals help you do it better and leverage the benefits of big data insights. Professional big data experts help you get the benefits of data insights to improve your business performance.

The next path to the insights of data is Predictive analytics. It utilizes multiple statistical approaches and machine learning techniques to help businesses predict future events.

The point to note here is that it is just a predictive analysis based on probabilities, so it doesn’t provide accurate outcomes. This analytics just gives outcomes based on descriptive analytics.

Now come to prescriptive analytics. It shows the possible actions you can take based on descriptive and predictive analysis. Prescriptive analytics combines the business rules you have in your organization, data insights and different mathematical models to support decision making and get better results.

Organizations are free to use these analytical approaches as per their need and customer’s experience they want to offer. This analytics is not department-centred. Organizations can implement this business analytical approach in any department. From sales to customer support, this analytics will help get the best outcomes.

You should keep in mind that business analytics needs the required amount of high-quality and relevant data. It is essential for the organizations seeking for accurate outcomes with analytics and insights of data.

A deep insight into data analytics

The process of collecting and analyzing raw data to get relevant and valuable information is known as data analytics. Businesses worldwide collect huge data, including transportation, logistics, sales figures and market research data.

One of the major benefits of data analytics is it helps you identify the risks, trends and available opportunities. Data analytics enables businesses to easily modify and update their existing processes with the extracted outcomes to make better decisions.

This could help you figure the time of new product launch, examining the effectiveness of new products and developing the required strategies for sustainable growth and development of business.

Now most of the data analysis is done through automation tools and techniques. The widespread accessibility of multiple tools, and platforms, help data analysts to minimize the time of data analysis.

The techniques used by data analysts are as follows:

  • Data mining: It incorporates sorting or arranging through big data sets to analyze and identify relationships, patterns, risks and trends.
  • Predictive analysis: Experts analyze and combine historical data and provide better results with predictive analysis.
  • Machine Learning: Statistical probabilities are used to teach machines (computers) for faster data processing.
  • Big data analytics: Uses machine learning tools, data mining and the predictive analysis study to convert raw data into the business intelligence.
  • Text mining: Analysis trends, behaviors and patterns in text-based content, emails and other documents.

In fact, many organizations worldwide are moving their data to the cloud, doing this helping them with faster data upload, transfer and accessibility. Cloud technologies offer different services such as data upload, data transfer and data accessibility to the businesses.

Business Analytics vs Data Analytics

Let’s check some of the basic comparisons between business analytics vs data analytics:


A business analyst creates the trends in data, KPIs (Key Performance Indexes) matrix, and data reports to assist organizations. While a data analyst builds models, find correlations and patterns to see the data outcomes.


Both business analysts and data analysts work with data and give better solutions to organizations for better growth and performance. Business analysts use data to make strategic decisions required for an organization.

Data analysts collect and manipulate data, draw useful information from it, and turn this information into valuable insights.


Business analysts do a comparative and static study of data. On the other hand, a data analyst does deep data analysis and implements data mining and gives a better visual representation of data.

Data Quality

Business analytics – data as a single version of fact.

Data analytics – multiple datasets used for deep study and practical analysis.

Data Model

In business analytics professionals move on with schema on the load data model. Whereas, in data, analytics experts move on with schema on the query data model.


Business analysts do descriptive and retrospective analysis. In contrast, data analysts do prescriptive and predictive analysis.

Area of expertise

A business analyst should have expertise in requirement gathering and data modelling. Whereas, a data analyst must be proficient in data mining and business intelligence skills along with expertise in modern technologies such as AI (Artificial Intelligence) and ML (Machine Learning).

Desired degree

A business analyst must have a solid business administration background. He/she should come from IT, computer science, business management or associated fields. To be a data analyst, you must have an IT or math background. You must have proficiency in databases, algorithms and complex statistics.

Final Words

In this study, we have tried to describe some of the basic differences between business analytics vs data analytics. Both have their own importance and values in an organization.

Business analytics and data analytics both work to increase the growth, development and performance of organizations. These analytical approaches use different methods and approaches to fulfil multiple motives of your business.