Difference between business analytics and data science

Business analytics and data science are terms often used interchangeably, but the truth is far from it. Business analytics is mostly focused on helping companies make business decisions. It involves gathering data, analyzing it, and finding patterns that can be used to predict future outcomes.

Data science is also a broader field than business analytics because it involves more than just predicting future events. Data scientists can use their skills to help a company understand its customers better or even make decisions about how to improve its products and services.

So what’s the difference between business analytics and data science? For starters, business analytics tend to be focused on making decisions about things that have already happened. Whereas, data science tends to be focused on making predictions about what will happen in the future!

What is business analytics? 

Business analytics collects, analyses, and interprets data to make better business decisions. The relevance of business analytics can be seen in virtually every industry. The ability to collect and analyze data allows companies to make decisions in real-time.

For example, a retailer may need information about its customers’ purchasing patterns to determine what products need to be stocked on the shelves for the best sales results.

READ MORE: What is Business Analytics: An overview

What is data science?

Data science is the study of data, a field that has grown rapidly in the last few years. As we’ve gone from an analog world to a digital one, there’s been an increasing need for people who can collect and analyze information from large databases to make decisions and take action.

Companies use data science and business analytics in multiple ways—to predict customer behavior, optimize advertising campaigns, analyze business processes, improve product quality control, and much more.

Data science and business analytics have been applied in many industries, but perhaps the most prominent example is finance. In the 1990s, banks began using large customer information databases to predict which customers were likely to default on their loans. This made it possible for banks to offer credit cards with lower interest rates while still making money off them.

Since then, data science and business analytics have spread across all areas of finance and business management. Companies like Google and Facebook have hired hundreds of data scientists to help them make their businesses more efficient by analyzing user behavior patterns.

Job role: Business Analyst vs Data Scientist

Business Analyst	Data Scientist
Don’t require the ability to code	Require the knowledge of coding
Focused on making decisions based on their knowledge of an organization’s operations and needs	Use advanced statistical analysis techniques to find patterns in the data they collect.
Use software like Excel, PowerPoint, and Word	Rely on programming languages like Python or R for most of their work
Focus on organizational problems related to strategy and planning	Concerned with analyzing large datasets in order to find new insights into how companies operate.
Generally trained in business administration or economics	Tend to come from computer science or statistics backgrounds.
Work with both qualitative and quantitative data	Tends to be more focused on quantitative analysis only
Responsible for collecting data through surveys or other methods	May be responsible for designing experiments or analyzing large amounts of unstructured information such as social media posts or emails.
Spend most of their time working on projects that have already been defined by others within the organization	Spend most of their time working on projects that have been defined by themselves

Role of a business analyst

Business analysts are the unsung heroes of business. They are often the people who bring a company’s vision to life. However, they often don’t get the credit they deserve. Here are some of their roles and responsibilities –

• They craft the user experience for new products or software, looking at how people will use it and how it will fit in their lives.
• They make sure that software works as efficiently as possible by testing it extensively, ensuring it conforms to industry standards and making sure that it is easy to use and understand.
• They identify problems with existing software before they cause real damage to companies or users.
• They work with developers on creating new features for existing software.

Role of a data scientist

The role of a data scientist varies depending on where they work; however, there are some roles and responsibilities of a data scientist –

• They are the ones who make sense of the data.
• They have a strong understanding of statistics, machine learning, and business knowledge.
• Data scientist is a generalist position requiring technical expertise and business acumen.
• They are responsible for collecting, cleaning, processing, and analyzing data to gain useful insights for decision-making processes.
• They need to understand complex problems quickly, determine how best to solve them, and communicate their findings efficiently.
• They are responsible for analyzing large volumes of data and translating it into meaningful information for decision-makers within an organization.

Skills and tools: Business Analyst vs Data Scientist

Data Scientist	Business Analyst
Have more of an academic background and focus on statistical analysis and machine learning.	Concerned with the business side of things: identifying opportunities, analyzing problems, and recommending solutions
Use programming languages like Python and R	Use Excel spreadsheets and PowerPoint presentations.
Have a higher salary than business analysts	Have a relatively lower salary.
Work in teams with other analysts or programmers	Tend to work alone or in pairs with other people who have similar responsibilities (like project managers)

Skills required for a business analyst

Business analysts work with developers, designers, and other team members to ensure that what they are building is what their clients want and need.

To do all of this, they need the following skills –

• An ability to understand the business problem
• An understanding of the project’s scope
• Excellent communication skills
• A working knowledge of the software development process
• A good understanding of IT systems and infrastructure
• Must be able to communicate effectively in both written and oral form
• Must have good time management skills
• Must have analytical skills

Skills required for a data scientist

To become a data scientist, you’ll need a wide range of skills and knowledge. Here are some of the most important skills –

• Knowledge of programming languages like Python, R, SQL, and others. The more languages you know, the better!
• Experience with machine learning algorithms such as neural networks, support vector machines, and decision trees. These are some of the most commonly used algorithms by data scientists today.
• Experience with big data tools like Hadoop or Spark can also come in handy!

Quick read: Best resources to master data science

Career opportunities: Business analyst vs data scientist 

The demand for business analysts and data scientists is at an all-time high. The two careers have many similarities: both require soft skills like communication and problem-solving skills and a deep understanding of statistics and computer science principles. However, some differences between the two careers set them apart.

Career opportunities for a business analyst

Business analysts usually work closely with other departments such as marketing, sales, IT, finance, and human resources to deliver quality products or services.

Look it up: How is business analytics changing the world?

Business analyst jobs are available at all levels of the organization, including entry-level positions like junior analysts or senior management positions such as enterprise analyst or enterprise architect roles. Some companies offer leadership development programs where employees can advance their careers by moving up through various management positions within their company or even moving up into a higher level position with another company entirely.

• Financial Analyst: Analyse financial data to support investment decisions, risk assessment, and financial planning. 
• Operations Analyst: Optimize supply chain, logistics, and operations by analysing data to improve efficiency and reduce costs. 
• Digital Marketing Analyst: Use data to measure and optimize digital marketing campaigns, customer acquisition, and website performance. 
• Customer Relationship Manager (CRM): Manage customer data and use it to enhance customer experiences, retention, and loyalty. 
• Healthcare Data Analyst: Analyse healthcare data to improve patient outcomes, optimize hospital operations, and assess healthcare costs. 
• Consultant: Work as a data analytics consultant, providing data-driven solutions to clients in various industries. 
• Risk Analyst: Assess and mitigate financial and operational risks by analysing data and developing risk models. 

Career opportunities for a data scientist 

Data scientists are in demand. The field is growing rapidly, and the opportunities for data scientists are plentiful. There are many career opportunities for a data scientist. A data scientist can work at a large, small company or even as an independent consultant. 

Here are some of the most common roles for data scientists –

• Data Scientist: Develop and apply machine learning models and statistical techniques to extract insights and solve complex business problems. 
• Machine Learning Engineer: Focus on designing, building, and deploying machine learning models and algorithms for predictive and prescriptive analytics. 
• Data Analyst: Collect, clean, and analyse data to provide actionable insights and support decision-making processes. 
• Business Intelligence Analyst: Create interactive reports and dashboards to visualize data and facilitate data-driven decision-making. 
• Data Engineer: Build and manage data pipelines, databases, and data infrastructure to ensure efficient data processing and storage. 
• Quantitative Analyst (Quant): Work in finance to develop mathematical models and trading strategies to optimize investment decisions. 

A data scientist may also need to create reports to help management understand how well their business is performing financially compared to competitors within their industry or globally across all industries.

Salary comparison: Business analyst vs. data scientist

The salary of a business analyst and data scientist is based on the experience and education of the employee. However, many factors determine your salary as a business analyst or data scientist. These factors include the type of company you work for and whether or not you have a degree in computer science or another related field.

Salary of a business analyst

The average salary of a business analyst in India is INR 9.7 LPA. If you are looking for more specific numbers, you can use sites like Glassdoor, which will show you the salaries for specific companies in your area. Another factor to consider when calculating your salary is whether or not you have experience with any particular programming languages or techniques; if so, then that’s something that should be reflected in your salary negotiations.

Salary of a data scientist

The average annual salary for data scientists in India is INR 14 LPA, depending on their expertise and experience with different tools such as Python or SQL. The same applies here as it does to business analysts. If you have experience using certain tools or programming languages, then it will help increase your earning potential since these skills are harder to find in other applicants.

YOU MAY ALSO LIKE: Data Analyst vs Business Analyst: What’s the difference?

How to become a business analyst?

Many career paths can lead to becoming a business analyst. Still, the most direct way is to earn an undergraduate degree in business administration or a related field. Students who have earned a bachelor’s degree can apply for graduate school and pursue an MBA in business analysis or M.Sc. in Business Analytics.

Business analysts must be able to think critically, so they may want to take classes that help them understand how businesses function. These classes usually include economics, marketing, finance, and accounting. Students who do not have a business background can also take these courses if they are interested in learning more about how companies operate. In addition, art classes such as English composition will help students write effective reports and presentations when they enter the workforce as business analysts.

In addition to taking courses that build their knowledge base, it is important for students interested in becoming business analysts to gain experience working in offices or other environments where they will be exposed to various types of technologies used by businesses today, such as computers and software programs that assist companies with operations such as payroll services or inventory management programs, for example. 

In addition, some colleges offer internships for students interested in pursuing careers as future leaders within their organisation once they graduate from college, so this might be worth looking into if you are really serious about becoming a business analyst.

READ MORE: Here’s how to become a business analyst?

How to become a data scientist?

The first step to becoming a data scientist is to choose the right course. There are many courses available for those who want to become business analysts. The first step is to determine which course suits you best.

The Master of Business Administration (MBA) program is one of the most popular courses. It takes around two years to complete this course, and during this time, you will be trained in various areas such as management, marketing, and finance. You will also learn how to use various tools such as Excel and Powerpoint that are necessary to become a successful business analyst.

Another popular option is the Master of Science in Data Science . This programme lasts two years and covers database management systems and software engineering topics.

Some people prefer taking short-term courses after undergraduate degrees instead of going straight into postgraduate studies because they feel they need more experience before applying for jobs in this field. If you’re among them, you can choose an online MBA from Manipal Academy of Higher Education that offers specializations in business analytics and data science.

There are also some online courses available that can help prepare students for careers as data scientists. Still, these should only be taken if you have already gained experience working with computers since many companies require applicants to have a background in computer science.

If you are still unsure if you should pursue an MBA or M.Sc. degree, then speak to your career counsellor at school and ask them for their advice.

Hone your skills with Online Manipal

Business Analytics, Data Science and Big Data are some of the most in-demand skills in today’s workforce.  And the programs by Manipal Academy of Higher Education (MAHE) at Online Manipal can help you achieve just that.

Our online master’s degree in Business Analytics and Data Science will prepare you for an analyst or data scientist career. Using unstructured and structured data, you’ll learn how to use statistical analysis to solve business problems, communicate findings to non-technical audiences, and analyse big data sets. You’ll also learn how to use machine learning algorithms to automate decision-making processes and extract insights from large datasets. 

Online programmes at Online Manipal are taught by faculty who specialise in their fields and have worked at some of the world’s largest companies. They are dedicated professionals who want their students to succeed—no matter where they are!

Our online master’s degree in Data Science offers a comprehensive curriculum that covers all aspects of the field from databases through visualisation techniques, machine learning algorithms, and natural language processing applications through case studies on real-world data sets.

Conclusion

You can master your skills and learn more about business analytics and data science with the best courses offered by Manipal Academy of Higher Education (MAHE) through  Online Manipal. You can either choose to pursue an online MSc in Data Science or an online MSc in Business Analytics from MAHE. It will help you gain the skills you need to succeed in various roles and industries. Our courses are designed to help you develop the necessary expertise to be effective in your role while also providing you with a foundation for further study.