Business Analytics vs Data Analytics

Business Analytics vs Data Analytics

Data Analytics vs Business Analytics

Business Analytics vs Data Analytics

Business Analytics vs Data Analytics

Business Analytics vs Data Analytics


Business Analytics vs Data Analytics


Business Analytics vs Data Analytics

Data is simply changing the way that we shop, eat, vote, search, or even whom we marry. Today, we generate large volumes of data invaluable to companies, shops, restaurants, and websites. Analytics is the language of data. It allows us to talk to data and, more importantly, listen to what it tells us.


This becomes especially critical in today’s workplace. Where data surrounds us. by learning to listen to it; we can uncover hidden trends and insights that ultimately allow us to make better business decisions.


What makes analytics truly amazing is that any system that generates data is a potential information goldmine. This could be a small household, a multi-million-dollar company, the snack food stall down the road, or even your own Facebook account.


So why is analytics so important?

It’s because, with the tsunami of information available, companies need data analytics specialists or data scientists to control, manage and make sense of it all. But there aren’t enough data scientists available for all the data.


Scientists worldwide would still not fill even 20% of the current demand. This is why switching to a career in analytics and big data can be one of the most interesting and lucrative choices you can make.


What is Data Analytics?

Companies are constantly collecting huge amounts of data. But in its raw form, this data doesn’t mean anything. Data analytics is the practice of examining raw data to get business-useful insights. These insights are super important to drive smart business decisions.


What a data analyst does is take all this complex jigsaw of data. They take it out and make it something you can use. Analysts can pass these insights on to the company. After interpreting the data, you can then make the most informed decisions.


You can think of data analytics as a kind of business intelligence used to solve every company’s problems and challenges. It’s all about finding patterns in the data to tell you something useful or relevant about the business operations.


So, for instance, how customers engage with a particular product or employees engage with a particular tool armed with data insights. Companies are then able to make better decisions about their audience, a company as a whole and the industry in which they work.


Data is everywhere, so it actually has an infinite amount of uses across all kinds of businesses and organizations globally. Data analytics is used to make faster and better business decisions to reduce overall business costs and to develop new and innovative products and services.


in more specific terms, data analytics might be used to do the following.

to predict future sales

purchasing behaviors for security purposes to help and protect against fraud

to analyze the effectiveness of marketing campaigns

to boost customer acquisition and retention

to increase supply chain efficiency


Data Analytics and data analysis are not the same. Click here to learn more about data analysis.


What is Business Analytics?

Data is one of the most valuable resources in today’s ever-changing market. Across industries, professionals collect, analyze, and interpret data to inform decisions and drive organizational performance. This process is called business analytics.

Let’s see the four types of business analytics

➤ descriptive

➤ diagnostic

➤ predictive

➤ prescriptive


Descriptive analytics

Descriptive analytics serves as the foundation and answers the question, what happened? It does so using current and historical data to describe trends and relationships. Descriptive analytics is especially effective for communicating change over time, such as tracking and reporting a business’s website traffic.


Diagnostic analytics

The next logical question is– why did this happen? Diagnostic analytics answers that. It helps determine the root cause of trends and correlations between variables. For example, a meal kit delivery company can gather data on why people cancel subscriptions to improve its products and services and retain customers.


Predictive analytics

Predictive analytics have answers for the question, what might happen in the future? It utilizes past data to forecast scenarios, trends, and events to inform business strategies. For instance, marketers can use prior years’ data to forecast sales trends and plan campaigns accordingly.


Prescriptive analytics

Prescriptive analytics tells what to do next. It involves considering all relevant data to chart an optimal path forward. Product managers for a new mobile app can employ beta testing to determine which features to include or exclude to optimize the user experience.


Leveraging these business analytics types in pairs can provide a full picture of the story data tells and lead to more informed decision-making.


Difference between Business analytics and data analytics

We often have a question – is business analytics and data analytics same? They both work on the data but there are a few key differences in their approach.


Let’s see some of the key data analytics and business analytics differences:

TopicData AnalyticsBusiness Analytics
FocusIt focuses on analyzing and drawing insights from raw dataIt focuses on applying those insights to solve specific business problems
ObjectiveAims to uncover patterns, correlations, and trends in large data setsAims to optimize business operations, improve decision-making, and drive growth and profitability
SkillsRequires strong statistical and computational skills to analyze and interpret dataRequires a deep understanding of business operations and strategy in addition to analytical skills
TechniquesUtilizes statistical and computational techniques to analyze dataUtilizes techniques such as predictive modeling, data visualization, and performance metrics to inform decision-making
OutputsData models and visualizations that communicate insightsActionable insights that can drive business value



Difference between data analyst and Business Analyst

Who is a business analyst? 
As the name implies, a business analyst profile is more concerned with the data’s business implications. he uses data to help streamline and improve the business metrics of the organization, like,

revenue generation

marketing operations

resource allocations

He tends to answer questions like

what a business need?

what problems it is facing?

how to optimize its operations?


Who is a data analyst? 
A data analyst is a person who collects, analyzes, and interprets numeric data using statistical tools and turns them into meaningful language. He creates reports and visual presentations to make strategic business decisions easily.


Although both business analysts and data analysts work with the data, the difference lies in what they do with it. The ultimate goal of a business analyst is to help make practical and concrete decisions for an organization. The end goal of a data analyst is to gather and analyze data for the business to evaluate and use to make decisions on their own.


Now let’s compare the two based on the skill set they possess.

Business analyst

analytical skills

    ⮚ feasibility analysis

    ⮚ SWOT analysis

    ⮚ interface analysis

computer skills

    ⮚ MS PowerPoint

    ⮚ MS Excel

    ⮚ and other Microsoft applications

problem-solving skills

critical thinking skills and

interpersonal communication skills


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Data analysts

strong analytical skills

data warehousing

Adobe and Google Analytics

programming knowledge

     ⮚ Python

     ⮚ R language

     ⮚ reporting

data visualization

statistical knowledge

SQL or database knowledge

spreadsheet knowledge


Now that you completely understand what skills are necessary for becoming a business analyst and data analyst let us delve deeper and look into the roles and responsibilities.


Business analysts role

understanding the requirements of the business

analyzing information

documenting the findings

evaluating and implementing the finest solution


The roles of a data analyst

mining data from primary and secondary sources

cleaning data to get rid of irrelevant information

analyzing the results using statistical tools

interpreting results

creating data reports and virtual presentations


Now let’s see business analyst vs data analyst salary.

A data analyst owns an average salary of dollar 50,000$ 70,000$ per annum

A business analyst owns a slightly higher average annual salary of 80,000$ to 90,000$.


The top companies hiring for the positions of business analyst and data analyst are

axial wave

pro Amazon Deloitte and




Every company, from the newest startups to well-established multinational corporations, must use data to drive innovation and growth. With some key distinctions, business and data analytics have the same objective of optimizing data to increase effectiveness and solve issues.


Whichever route you take, you’ll need to swiftly, efficiently, and securely collect reliable data from a variety of sources. Technogeeks provides the best environment to grow your analytical skills in the route of your choice. Even if you are unsure, our counselors can help you choose one. Check out our course page below and get ready to dive into the world of analytics!



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