Getting A Master’s in Data Analytics: What You Need to Know

A master’s in data analytics prepares degree holders for a career within the field of data analytics, whether they're an established professional or someone looking to start a new career. As a result, a Master's of Science (MS) in Data Analytics programme can cover introductory to advanced courses, providing an opportunity for course takers to learn new skills or deepen old ones.

Read on to learn more about master’s degrees in data analytics, whether you should consider pursuing one, and the different types of degrees available to you. 

Master’s degree in data analytics

A master's degree in data analytics is typically designed either for individuals who are looking to enter the field through a career shift or who want to advance their current career by attaining a higher educational qualification. In effect, a master's degree in data analytics can either supplement undergraduate work in the field or provide groundwork for a career shift for those who have studied another discipline.

Master’s vs bachelor’s degree in data analytics 

A master’s degree shares many similarities with a bachelor’s degree in data analytics. But, some key differences exist that degree seekers should keep in mind.

Generally, both a master’s degree and a bachelor’s degree in data analytics will cover much of the same material, such as data analysis, computer science, and statistics. However, some master's programmes may cover these topics in greater depth than what you would encounter in an undergraduate course of study.

But, while the programmes might cover much of the same material, they usually do so within very different timelines. For example, while a bachelor's degree usually takes four or more years to complete, a master's degree can take two years to complete, depending on the programme, your course load, and whether you're a full- or part-time student. In order to enrol in a master's programme, though, you'll already need to have a bachelor's degree.

Curriculum

The exact curriculum that you’ll follow as a graduate student in data analytics will vary from programme to programme, but you can expect to take courses in common topics such as data analysis, statistics, computer science, and machine learning. 

To help you better understand what you can expect from a master’s programme, this example curriculum is from the Christ University programme [1]:

• Courses on topics such as computer science, statistics, and statistics electives. Required courses include:

  • Principles of Data Analytics

  • Statistical Methods using R

  • Python for Data Analytics

  • Mathematical Foundation for Data Analytics

  • Database Technologies

  • Data mining

  • Machine Learning

  • Natural Language Processing

  • Data visualisation

Is a Master’s in Data Analytics worth it? 

Depending on your own goals, resources, and background, an MS in data analytics could be well worth the effort. Or, it could be an unnecessary detour. Typically, a master’s is well-suited to individuals who don’t already possess a bachelor’s degree in data analytics or who wish to continue studying data analytics from an academic perspective. Individuals who previously received a bachelor’s degree in a related field like statistics or computer science, might consider obtaining a master’s in data analytics in order to gain a deeper understanding of the field and to market their skill set to potential employers. 

According to research conducted by 365 Data Science, the percentages of data scientists with a bachelor’s, master’s, or doctoral degree are as follows [2]:

• Bachelor’s degree: 34 percent

• Master’s degree: 50 percent 

• Doctoral or professional degree: 6 percent

This educational breakdown suggests that a bachelor’s degree could be sufficient for job seekers to land a role. However, a master’s could positively highlight your skills and abilities to employers, making you a more competitive applicant overall. In some cases, an employer may even explicitly require a master’s degree for senior positions. 

Master’s in data analytics salary 

Data scientists make above the average salary, with an average of ₹13,00,000 annually [3]. A master’s degree in data analytics or a related profession could have a positive impact on your earning potential.

Data analytics jobs

A variety of jobs exist that a degree in data analytics can prepare you for. While some of these jobs can be attained with a data analytics bachelor’s degree, more senior roles may require an advanced degree, such as a master’s degree. 

Some of the positions you might consider pursuing with a master’s in data analytics, along with annual salary averages from Glassdoor, include: 

• Data analyst: ₹6,50,000 

• Business analyst: ₹8,00,000 

• Data scientist: ₹14,00,000 

• Statistician: ₹4,13,000 

• Business systems analyst: ₹10,00,000

• Business intelligence analyst: ₹7,45,000

Masters in data analytics programme comparisons

Just as you may have numerous reasons to pursue a master’s degree in data analytics, you also have a wide range of different types of master's degrees that you can pursue. If you’re considering a future as a graduate student, you’ll want to consider these three types of programmes before applying:

In-person master’s degree in data analytics 

An in-person master’s degree is a programme in which you attend classes alongside your peers in a real-world classroom. As a result, this option provides a more traditional university experience, which includes more face-to-face time with your peers and instructors, often allowing you to have more direct guidance and networking opportunities. However, in-person degrees often cost more and are more rigidly structured than other programme types. 

Master’s in data analytics online

Online master’s programmes are becoming increasingly popular due to the flexibility they provide course takers and their often lower cost of attendance. While some programmes may follow traditional application timelines, others might have more relaxed admissions requirements that allow applicants to apply on a rolling basis. However, while these programmes usually provide more flexible schedules and cost less, there may be less opportunity for networking and mentorship than more traditional options. 

Hybrid programmes 

A hybrid graduate programme pairs elements of in-person and online programmes to provide a greater degree of flexibility in completing course material while also allowing for more networking opportunities. Depending on your circumstances and personal objectives, a programme of this nature could either offer the best of both worlds, or be a more compromised version of your ideal programme that doesn’t fit your needs. 

Learn more about data analytics on Coursera 

A master’s degree in data analytics is an effective way to further develop your skills and position yourself for more advanced roles in the data analytics field. If you're considering a career in data analytics, you might consider taking an online specialisation through Coursera to learn more. 

The University of Michigan’s Data Analytics in the Public Sector with R Specialization equips learners with fundamental technical skills using the R programming language to gather, manipulate, analyse, visualise, and interpret data to inform public policy and public administrative functions.

Macquarie University's Excel Skills for Data Analytics and Visualization Specialization teaches course takers how to bring data to life using advanced Excel functions, creative visualisations, and powerful automation features.