Data science is steadily establishing itself as a new parallel alongside Computer Science but with extensive applications in the fields of Finance, Statistics, Economics, Communication and Law, among others. As new spheres of research come up, for instance, data-based public health management systems, the attractiveness of data science and analytics as a career is only going to rise. Not just that, straightaway or after a few years of industry experience, Data Analytics experts can also shift towards allied spaces of Artificial Intelligence and Machine Learning.
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About Data Analytics
Digging deeper into how Data Analytics is put to use by organisations, we found some interesting results. From descriptive analytical tools that help in better representation of data, e.g. data visualisation to prescriptive analysis which includes forecasting software, it is influencing major business decisions. Be it at the planning stage, organising or deviation-correction, companies, in whatever capacity they can, are using such tools to carry out pattern formation and interpretation, etc.
- In financial enterprises engaged in wealth management, advisory or trading, Data Analytics is used in the identification of profit-making opportunities, goals and financial instrument matching, assessment of risks, etc.
- In technology companies, tools of data analysis are put to a grinding test through the development of data infrastructure, data mining, information and data process management and so forth.
- In research organisations, Data Analytics plays a key role in the collection, analysis and interpretation of data. Themes may include public opinion, behavioural analysis, environmental awareness, etc.
- In other corporations, typical usage of Data Analytics ranges from market research, identification of new verticals and customer trends to advanced spaces of big data, machine learning and fraudulent practices.
To build a solid career in Data Analytics, a combination of technical understanding and a knack for creativity is of paramount importance. While there is no dearth of opportunities in this sector and companies hiring individuals by scores, having the right set of knowledge and career skills paves the way for a successful profession. Here are a few steps you can follow.
Earn a Degree
Being a heavily quantitative and intensive field of study, an advanced qualification related to mathematics, statistics, computer science engineering or other similar areas, for instance, MSc Computer Science keeps you in good stead. Further, you may also go for specific Data Analytics courses such as an MSc or MBA in Data Analytics. As it has a wide range of options to choose from like decision analytics, health or energy analytics and Clinical Data Management among others, whatever you end up with, make sure to maintain an above-average score. In due course, a handful of students also enrol for a PhD in Computer Science, data science, etc or parallelly for degrees in public affairs, public policy such as a Master in Public Health or Master in Public Administration [MPA].
Discover & Develop your Interests
Whether it is in corporate domain or a career in research as that of a research assistant, and core Data Analytics or other related fields, find and work towards your interests and niche. Find the right track/specialisation which accentuates your skills and abilities. You can do this by taking up electives, project work or audit courses or even online modules.
Intermediate to advanced proficiency in at least two programming languages makes you stand out from the crowd. Python, R, Java, C, MATLAB, etc are some that are considered quite popular in the industry. Further, you can also go for data visualisation tools and database management software like Oracle DBMS, etc.
Get Involved in Projects, Internships and Assistantships
During the course, getting engaged in short or long-term projects and training programs like internships is as important as covering the practised syllabus of data science. This aids in developing a practical outlook, an introduction to real-world challenges and a brilliant learning experience. Moreover, getting involved with professors and professionals adds to the strength of your resume in no other way.
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Career Profiles in Data Analytics
The growth in this sector is quite multidimensional. This is, so to say, due to the heavy diversification and rise in new verticals as well as the demand for professionals across from entry to senior level. Further, the skills gained working in data-related capacities lends you transferable skills, those which can be applied to any number of industries and roles. Here are a few prominent career profiles we consider as amongst the most popular at the present.
Data Visualisation Expert
Popular data visualisation tools including but not limited to Tableau and Microsoft PowerBI are increasingly being used in the dissemination of knowledge in the form of interactive dashboards. While multinational enterprises, the United Nations and other international initiatives are some large scale organisations driving the implementation, many small scale companies are also shifting towards this. Typical responsibilities involve examination and alignment of huge bundles of data, making it understandable, highlighting relevant factors/indicators/correlations and combining different data sets, among others.
Healthcare Data Analyst
The deployment of Data Analytics in the health sector is growing each passing day. Be it improving public health infrastructure, better hospital management systems, clinical data storage and retrieval and so forth, as a healthcare data analyst, you can work in a range of capacities across industries and alongside doctors, medical professionals, paramedics and public health experts.
As mentioned above, companies engaged in the financial sector make heavy use of Data Analytics in order to understand and make sense of market trends, stock fluctuation and volatility. Moreover, the nature of responsibilities also vary among private equity firms, hedge funds, wealth management advisories, investment banks, credit rating agencies. Spotting profit-making avenues, forecasting, technical and fundamental analysis, etc are some of the tasks you can expect to perform. To know more, read our blog on Equity Research Analyst.
Data Analyst/Data Scientist
Considered as one of the dream jobs in the Data Analytics sector, the job of a data analyst or data scientist is tasked with end-to-end setting up and management of data structures, data architecture, business intelligence and a host of other responsibilities. They help businesses in making vital decisions through better collection, representation and interpretation of data. Being proficient in programming tools, data visualisation software applications and statistical methods is a strong recommendation and there are innumerable industries to choose from. A data scientist is generally considered above a data analyst in the pecking order. Read more about Technology Analyst at our exclusive blog.
Operating in higher-level echelons of management, as a consultant, you work in actual client-facing scenarios and advise them on a particular course of actions. Furthermore, it also involves regular interaction with planning professionals, operations analysts, senior partners and other senior executives on the formulation of plans, delving into different business verticals, collaboration with diverse businesses, etc. Many consultants work remotely and primarily engage in client meetings on a daily basis. As this is a highly remunerative job, an advanced degree, for instance, an MBA in Data Science, along with 5-7 years of industry experience is desired.
The field of actuarial science has witnessed unprecedented growth in the past decade especially with the promise of lucrative job opportunities on offer. Primarily, it involves heavy use of quantitative analysis in the shape of statistics and mathematical tools to understand, interpret and quantify risk situations. In other words, they help in assigning values to a number of insurance products and schemes. Actuarial analysts are not just in demand in insurance companies but can also move towards financial analysis, equity research, etc.
Crime and Fraud Analyst
Investigation and governance authorities are employing Data Analytics to assist in a crime or fraud-related issues. Typical responsibilities in this capacity may range from analysis of crime scenes, trends and patterns to logistical fraud data support, devising preventive measures and curative provision. As banking institutions are also dealing with numerous fraud concerns, they require expert professionals to secure backend data infrastructure as well as dealing with the resolution of fraudulent activities.
Machine Learning Analyst
This is usually considered as an advanced level position wherein individuals work in applying concepts of machine learning in numerous fields. Examples include self-driving cars, hiring processes, buying of raw materials, online recommendation, medical operation assistance, 3D printing and much more. As a machine learning analyst, you will work with learning methods such as supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning, among others. You can also venture towards a career in artificial intelligence [AI] as machine learning is carefully intertwined with this field.
The sphere of marketing and sales is no longer limited to offline and door to door approach but has acquired a personal and organic outlook. This has largely been the result of the integration of Data Analytics into processes of lead generation, niche identification, unexplored methods, actual monitoring of performance, data-based suggestions and much more. In particular, as a marketing analyst, you can expect to work in spaces of social media, online marketing, customer targeting, etc. If you start as an entry-level analyst, there are ample opportunities to work your way to senior-level roles. Pursuing a Postgraduate Diploma in Business Analytics [PGDBA] may also substantially help your cause.
Other Career Pathways
The list of opportunities in Data Analytics does not end here. There are innumerable ways Data Analytics is being implemented by industries and firms. Take a look at some more professions you can explore.
- Project Manager
- Logistics Expert
- Business Analyst
- Strategy Analyst
- Social Media Data Analyst
- Credit Analyst
- Predictive Analytics Expert
- Statistical Analyst
- Security Analyst
- Database Analyst
- A/B Testing Analyst
- Excel Analyst
Skills Required in Data Analytics
Data Analytics is a unique amalgamation of hardcore technical skills with the ability to work in grinding and challenging environments. While there is no shortage of lucrative opportunities of career building, proficiency in the given industry-appreciated skills, having a goal and vision along with short term experiences in the shape of projects and internships is strongly recommended. Furthermore, continuously reviewing and updating oneself with the recent changes in the industry is also preferable.
- Communication Skills
- Modelling and mapping techniques
- Programming languages
- Leadership Skills
- Quantitative as well as qualitative analysis
- Problem Solving
- Web-based Data Analytics tools like Google Analytics
- Project Management
- Clear understanding of what data can and can’t do.
- Critical Thinking and Analysis
- Inclination to learn and experiment
- Experience in working with deadline-based environments [desired]
- A natural knack for working in creatively intensive situations
Major Universities Offering Courses in Data Analytics
With the growth and rising relevance of Data Analytics and other fields of computer science, course offerings across the globe have also burgeoned. Moreover, this is not just limited to the Ivy League colleges but includes a range of institutions spanning Europe, North America and Australia, to name a few. Students are informed that while some may incline towards research, some still are designed for professional level careers.
|Times Higher Education Ranking 2021
|Data Analytics [DA]
|Master of Science in Data Science
|MassachusettsInstitute ofTechnology [MIT]
|Bachelor of Science in Engineering-Process DA
|Imperial College London
|MSc Health DA & Machine Learning
|MSc Energy Systems & DAMSc Spatio-Temporal Analytics & Big Data Mining
|University of Toronto
|Master of Management Analytics
|The University ofMelbourne
|Grad. Certificate in Applied Analytics [Online]Master of Applied Analytics [Online]Prof. Certificate in Applied Analytics [Online]
|The University ofHong Kong
|BSc in Decision Analytics
|Technical Universityof Munich
|MSc Data Engineering and Analytics
|The Australian National University
|Grad. Diploma of Applied DAMaster of Applied DA
|The University ofWaikato
|BSc- major in DAGrad. Certificate in DA
Note: The above-mentioned list of Data Analytics universities and courses mentioned is not exhaustive.
Application & Admission
In order to study abroad in courses of Data Analytics, prospective students need to follow a specific application procedure. In particular, these universities accept applications in two-three admission cycles, namely fall [primary], winter [secondary] and summer [optional]. Duly filled applications in addition to submission of official SAT/GRE/GMAT or IELTS/TOEFL scores, official transcripts, CV, Statement of Purpose (SOP) and Letters of Recommendation (LOR), amongst others are required to be considered for a place in the incoming class. A scholarship essay or funding statement may also be required in case you wish to apply for scholarships schemes.
To reinstate, Data Analytics is being utilized where it was never thought to have any use and individuals are flocking towards owing to this quality. Needless to say, the right specialisation, course and university plays a major part in shaping one’s careers. Take the assistance of the AI-led approach at Leverage Edu which suggests unique choices based on a personalised examination of your skills and interests and you can also reach out to our team of industry experts and we’ll ensure that you make an informed decision towards a rewarding career.