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Komal
17 December, 2024
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Did you know that there are 5.5 billion internet users today? This accounts for approximately 68% of the global population. This figure represents the reach of the internet and how people around the world communicate and connect. Be it for any purpose, you name it, and you could find it there. This makes it a gold mine for organisations to collect data and find solutions for a problem statement. It is upon organisations to leverage this unlimited data and grow.
From healthcare to telecommunication, data plays an essential role across industries. Given this switch, it is clear that there is going to be a rise in demand for professionals pursuing an MBA degree with a specialisation in data science or business analytics. But which one should you pursue? Here is your complete guide to help you understand the differences and ultimately make the choice that fits your goals and interests. In this blog, we shall cover the curriculum, career opportunities, eligibility criteria, and more.
This two-year master’s programme would help you take leadership roles using analytics and artificial intelligence. This multidisciplinary programme would equip you with analytical tools and methodologies to solve business and social problems. Learn to identify patterns, gain insights, and develop business strategies using these tools and techniques. This specialisation extensively uses statistical analysis in all aspects of business.
Want to experience a collaboration of coding and management in your postgraduation? In a world where hiring in the data science industry has increased by 46%, this program covers data-related skills, teaching how to interpret organisational data, establish data management processes, and leverage data for informed business decisions. It also focuses on crafting business questions as testable hypotheses using statistical methods and creating validated regression models to predict outcomes based on attribute effects. Expertise will be gained in utilising modern statistical tools and software, including R, Python, Spark, Excel, MySQL, and Hadoop. Additionally, the MBA in Data Science course provides hands-on experience in visual analytics using software like Tableau.
Both of these MBA programmes allow professionals to make data-driven decisions. While you would find many similarities, their processes and skill sets differ. Let’s understand these differences through their benefits. Here are three advantages of each of the MBA programmes:
Versatile Skill Set: Gain blended knowledge of technical expertise, management, and corporate strategies. You would use statistical analysis to develop future business plans and improve existing ones.
Business-Oriented: Learn to improve business processes, reduce costs, and more. Your focus would be more on the organisation and how to identify new growth areas for it. Moreover, the outcome should be to use data to make informed decisions.
Strategy Focused: Also, learn to combine data and managerial strategies for the benefit of your organisation. You can make effective business strategies with your business acumen and analytical skills.
Also read: Your Complete Guide to an MBA in Business Analytics.
Cutting-Edge Technical Knowledge: This programme requires you to be good with coding. This would enhance your technical skills, ultimately leading to job opportunities with big data platforms.
High Demand in Tech-Driven Roles: The demand for data science is increasing daily. With the shift towards digitalisation, every organisation is becoming data-centric. This requires professionals who can analyse data and help the organisation make informed decisions.
Focus on Innovation: Learn to find innovative solutions to complex business issues. With advanced automotive AI and analytics prediction tools, you can help the organisation create creative business plans and stay ahead of competitors.
Both the MBA specialisations are polar apart yet closer to some of the basic subjects. Your destiny depends on your desired subjects and ability to teach you the essentials. Before selecting the colleges, you need to make sure that you select the right subject. Check out the sample of both subjects below.
This is a sample curriculum of the programme. It might vary depending on the university’s pedagogy and mode of learning.
| Semester 1 | Semester 2 |
| Quantitative Methods | Operations Management |
| Managerial Economics | Financial Management |
| Management Information Systems | Human Resource Management |
| Financial Accounting | Financial Analytics |
| Marketing Management | Optimisation Analytics |
| Statistical Analysis | Business Intelligence |
| Data Modelling | Research Methods |
| Computational Methods | Managerial Communication |
| Semester 3 | Semester 4 |
| Predictive Analysis | Strategic Management |
| Risk Management | Operations and Supply Chain Analytics |
| Marketing Analysis | HR Analytics |
| Data Mining | Big Data Analytics |
| Simulation Modelling | Ethical and Legal Aspects of Analytics |
| Analytics Systems Analysis & Design | Project Management |
| Industry Internship Programme | Analytics Capstone Project – Elective Paper |
Take a look at this sample curriculum. However, it might vary depending on the university. Please reach out to the university for the actual syllabus.
| Semester 1 | Semester 2 |
| Managerial Economics | Legal Aspects of Business |
| Statistics for Management | Business Research Methods |
| Professional Communication | Financial Management |
| Accounting for Managers | Human Resource Management |
| Marketing Management | Conflict Resolution and Management |
| Semester 3 | Semester 4 |
| Analytics for Decision-Making | Advanced Deep Learning |
| Data Engineering | Digital Marketing |
| Data Visualisation | Major Project |
| Introduction to Data Science | Management in Action – Social Economic and Ethical Issues |
| Minor Project | Supervised and Unsupervised Machine Learning |
| Professional Ethics | |
| Strategic Management |
Also read: Benefits of Doing MBA in Data Science Programme
If playing with data seems like fun, then you can pursue either of the MBA programmes. However, there is a catch. If you have a technical background, you can choose an MBA in Data science, which would involve coding, algorithms, and machine learning. But if you come from a non-technical background, you can pursue an MBA in Business Analytics for your higher education. This MBA programme is inclined towards professionals keen on collaborating their analytical skills with business strategy and management.
There has been an increase in demand for professionals with analytics and data science skills and knowledge. After both MBA programmes, let’s look at some of the most high-paying careers you can pursue.
In this role, you shall handle the business operations and processes. You are responsible for making it more efficient and effective. Also, you must analyse the data to solve business problems.
As a supply chain analyst, you would collaborate with all the teams to determine more efficient ways to improve the process. From inventory analysis to operation management and, finally analysing trends, you must perform these tasks daily.
The name clarifies the responsibility of this job role, which is to manage and build an organisation’s database. The role also includes creating data reports, evaluating databases, and more.
Your daily role includes studying market trends and analysing the shifts by analysing competitors’ data. Help your organisation find its best-performing products and services and their underlying reasons.
Study and interpret the complex data points to develop market intelligence and financial reports. This profile requires you to optimise the business’s overall performance.
As a data scientist, you are supposed to determine and find the hidden patterns within the datasets. These points would be used to make business decisions leading to business growth and optimisation.
As someone who understands data at their fingertips, your role is to maintain the infrastructure supporting the data analysis. You must also build databases and pipelines to avoid any bottlenecks in the business processes.
This job includes collecting, organising, storing, and sharing data for your organisation. You are responsible for leveraging these data points to leverage data flow throughout a product lifecycle.
You can also leverage your MBA in Data Science degree to pursue a research career. Many organisations conduct advanced research. As a data scientist in academia, your job role is to help advance the field.
As a machine learning engineer, you design and develop machine learning models. This would help the businesses tackle and find valuable points from the data to benefit an organisation’s business. It would empower the team to make informed decisions.
Also read: Top 8 Career Options After MBA in Data Science
‘Data is the new currency.’
Similar to money, today, data has become truly valuable. Whether you choose an MBA in Business Analytics or Data Science, both are highly dependent on data. One would equip you with analytical and statistical tools, and the other would enhance your AI and programming skills, respectively. You must choose the one that aligns the most with your goals and interests. Remember that both these programmes would empower you to make informed decisions and lead your business towards growth. Let the power of data unlock the gates of new opportunities for you.
