Over the last few years, fields such as Data Analytics and Data Science have been the centre of attention for international companies as well as in higher education. What is more, new survey findings suggest that the interest of tech-savvy employers in exploring the potential of these specialisations is growing.
According to the most recent study conducted by the Graduate Management Admission Council (GMAC), more than 70% of employers plan to hire Business and Management Masters graduates for roles connected to Data Analytics in 2018. At the same time, more than 50% of surveyed companies plan to hire Masters graduates in Data Analytics.
The survey also found that hiring demand for Master of Data Analytics graduates is most notable in the Asia Pacific region where over 60% of employers plan to hire specialists in the field. The interest of European and Latin American companies in recruiting graduates is also strong.
What is Data Analytics?
With the hype that comes along with the rising popularity of new tech-related jobs, it can be difficult to really grasp what Data Analytics is all about, especially for people who are yet to take their first steps in this field. Essentially, the data analyst’s job is to extract valuable information from data in its raw form. Combing through these enormous amounts of information should lead to discovering insights which can in turn help the company reach particular goals.
Read: Masters Degree in Data Science and Analytics
An important distinction to make is that although often used interchangeably, Data Analytics and Data Science are not exactly the same disciplines. In fact, most online sources you will find on the topic claim that Data Analytics is more specific and concentrated than Data Science. As Rick Delgado explained for news outlet InsideBIGDATA, “Data Analytics is generally more focused than Data Science because instead of just looking for connections between data, data analysts have a specific goal in mind.”
What are the possible career paths for Data Analytics graduates?
Data analysis can help organisations optimise certain processes and improve the overall efficiency of their business. For example, in healthcare, data analysis is being used to track as well as optimise patient flow, treatment, and equipment used in hospitals, explained content writer Avantika Monnappa for certification training provider Simplilearn. Other industries which increasingly implement Data Analytics tools in their work include gaming, energy management, as well as travel agencies.
Read: What Are the Best Data Science Courses?
To build a career in Data Analytics, students need to develop excellent analytical skills. They will need to become proficient in maths, statistics, and even programming. According to tech and science news source Digg, Python and R are the two most popular programming languages utilised by data analysts and data scientists at the moment. However, prospective Masters applicants with little to no technical background should not get scared off by similar tech-heavy talk. As an article published by Jigsaw Academy ingeniously said: “The path to becoming a good big data analyst is both an art and a science.” Good communication skills and a general predisposition towards quantitative subjects coupled with genuine interest in the field may form just the right blend for a career in Data Analytics.
What are the study options?
If you have read the previous paragraphs and now have a better idea of what Data Analytics is all about, you might be interested in finding out more about your study options in this field. People who are set on continuing their education with a Masters degree will be glad to find out that graduate opportunities in Data Analytics are plentiful these days. Some internationally recognised universities which offer similar Masters programmes include Fordham University (US), EDHEC Business School (France), and the University of Warwick (UK).
Some of the programmes on offer are also interdisciplinary in nature and combine their technical focus with business courses which can be especially useful for future employment opportunities. This is precisely what Ilan Cohen who graduated from the MSc in Data Analytics and Digital Business at EDHEC in 2017 appreciated the most about his studies. “[I gained] knowledge that allows me to deal with complex analytical problems and to find solutions to real business cases,” he said. “Moreover, it helps me create a new mindset: to bridge the gap between data engineers and business managers.”
Next to Masters programmes, there are also flexible alternatives such as MOOCs, online courses, and bootcamps. The Data Science Bootcamp offered by IE Business School (Spain), for instance, is a shorter option for people who cannot commit to a full-time one-year programme. The 11-week bootcamp targets professionals with an average of between two and five years of work experience who have an analytical background. Participants can then learn to apply what they have learned in fields such as marketing, product development, project management, or general business administration.
What are the common admissions requirements?
As with any other field or programme, the entry requirements for Masters programmes in Data Analytics vary per university. Still, there are some general points to be expected such as an undergraduate diploma in a quantitative subject or in some cases, prior experience with maths or statistics. Although this is usually a common requirement, there are also institutions that welcome applicants with no analytical background at all. The Master of Science in Data Analytics at Fordham University is open for students who come from non-computer science areas as well.
When it comes to admissions tests, a GMAT or GRE score is also a common requirement for admission to most Masters in Data Analytics programmes. Check the official website of each programme you are considering because different schools will have their own preferences. For example, Fordham University recommends that applicants take the GRE, although they clarify that it is not obligatory. There is room for flexibility depending on what you are looking for as an applicant and what you want to gain from your study.
Are you convinced of the academic and career potential of Data Analytics yet? Explore your options further – the field has a lot more to offer!
