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Career in Data Analytics: Ultimate Guide

Career in Data Analytics: Ultimate Guide

Updated on 19 March, 2024

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• 14 min read

Table of Contents

Career in Data Analytics: What does a Data Analyst Do?
Why should I pursue a Career in Data Analytics?
Career in Data Analytics: What skills do I need to become a Data Analyst?
What are the tasks performed by Data Analysts?
How should you kick-start a Career in Data Analytics?
Conclusion

With data being at the core of the technology, data analytics has gained humongous popularity over the past few years and has become a hot topic in the market. With billions of data getting generated every day, demand for data analysts with the right skill set and knowledge will keep increasing. According to Harvard Business Review, data science is the sexiest job of the 21st century.

Data analytics is a growing career, the market is expected to expand. The market is projected to reach USD 655.53 billion by 2029 (Source). There are various employment opportunities in this field as the data is central to almost every industry and the organizations require professionals having an expertise in this field.

Data analytics is of high importance in the field as it helps the organizations in optimizing the data, and monitor the performances. This data helps in gaining better insights that aids in better results that are beneficial for organization’s growth.

Data analytics helps the businesses in understanding more about their customers that helps in adapting a customized approach.

There are various industries that benefit from the science of data analytics. The application lies in retail, manufacturing, entertainment, government, security, web applications, etc. People who are new to the industry and had the apprehension “What is data analytics?” must have gotten a fair understanding of the industry now.

Making a career in analytics is promising for people of all backgrounds, and there is an umpteenth number of opportunities that span across multiple industries for you to explore. According to IBM and Burning Glass insights, the number of positions for data analysts in the United States will increase to 2,720,000 by 2020. Keep reading this article if you want to understand who data analysts are, what they do, and how you can make a successful career in analytics.

Career in Data Analytics: What does a Data Analyst Do?

A data analyst gathers, processes, and analyzes the large volume of data from various sources to find meaningful patterns and insights, identify relevant questions, make predictions, and convert information into solutions to help the organization in the decision-making process. In layman’s language, data analysts convert raw data into meaningful information so that they can be consumed by organizations to grow their business. They prepare visual representation (charts, graphs, reports) of their findings to make it easy for others to understand.

A day-to-day data analyst role may differ based on the industry or domain that they are working in. In some organizations, analysts are also responsible for designing dashboards, maintaining databases and systems for various departments throughout an organization. A data analyst may also work with key stakeholders, top management, or other teams within the company. These include IT, finance, and database infrastructure to determine business goals and provide findings to achieve their goals.

Other set of responsibilities of a data analyst include gather or manage the data. Through the expertise they provide, they are able to predict and analyze the performance that helps in managing the resources and provide better results at much better cost.

Once the data research analyst have worked with the data, then they are required to communicate their findings to the relevant stakeholders that help in better understanding and business decision-making.

Why should I pursue a Career in Data Analytics?

According to the LinkedIn Workforce Report, there is an exponential increase in the demand for data analysts from 2015 to 2018. Besides demand, diversity also makes them easily fit in most industries such as finance, education, government sector, healthcare, IT, networking, etc.

Here is a list of few reasons that can help you in choosing data analytics as your career:

1. High demand – There is no use of data until it is put to the right use. To translate raw and unstructured data into meaningful insights, companies are continuously recruiting professionals who have the right knowledge of using advanced tools and good command over the programming language to design software that can process a large volume of datasets.

The data analysts are highly skilled and they help the organization in scaling, understanding the leakages and most importantly they also help in understanding their customers better.

These reasons also contribute to the data analysis professional being in high demand. Moreover, they also help in better cost- cutting measures as well as customizing the approach according to the users. There are various job opportunities available that help in making a successful career in data analytics.

2. High salary at entry-level and excellent perks – Being limited data analysts in the market, data analysts are paid very well in the industry even at entry-level. There is no denying that data analysis is one of the highest-paid jobs.

On average the salary procured by the data analyst are 4.3 lakhs per annum. The average salary ranges from 1.9 to 11.5 lakhs per annum (Source). As one progress in their career and focus on gaining skill sets, updating their knowledge and higher experience the salary bracket keeps expanding for them. One can enroll themselves into data analyst course and understand better of the industry.

The salary of a data analyst also depends upon the education level, a candidate’s experience, the industry that they work in, location, skills, and certifications.

3. Shortfall of Data Analyst Professionals – As stated above, the demand for a data analyst is very strong, but professionals who possess the right skill set and knowledge to perform the task are very limited. This opens up an extreme number of opportunities to kick start your career in this field.

Currently there is a high demand- supply gap for data professionals. Organizations require data professionals that help in gaining competitive edge over the competition. But there are not many professionals in the market today.

This results in high salary and successful career on the professional’s part. As the organization’s want to gain skilled professionals and they focus on giving them employee benefits and higher salary on retaining and acquiring their talents.

4. Diverse roles – Based on years of experience and skills, data analyst professionals are always exposed to versatile roles and responsibilities. There are numerous roles that you can choose from. All you need to do is identify your strength, what you are good at, and what exactly you want to do.

Checkout: Data Analyst Salary in India

Career in Data Analytics: What skills do I need to become a Data Analyst?

1. Programming Language

First and foremost, to become an expert in data analysis, you must have a solid understanding of at least one programming language. However, having command over more than one language makes you more versatile and increases your chances of getting a good salary. Some of the languages used by data analysts are python, R, Excel, and SQL. The trend keeps changing with technology, but the logic remains the same. It would be best if you focused on algorithms and fundamentals behind them to stay up to date.

The programming languages help in various efforts of the professionals. Not only working with the humungous data becomes easier but the programming languages also help in visualization, exploration and modelling of data.

2. Communication Skills

Insights that are gathered from data analysis are consumed by several departments within the company to aid decision-making. Hence, it is of utmost importance for a data analyst to convey their findings in a manner that is easy to understand for a vast audience. Strong presentation and communication skills are the keys to success.

The data analysts are required to present the insights to the stakeholders that helps in better decision making. If a data analyst is not an able communicator, then that creates a communication gap which is not ideal at all.

3. Database Knowledge

Being a data analyst, you may have to work at the backend wherein you design a data warehouse to store a huge chunk of data from multiple sources in one place. You must possess a strong database and database query language knowledge to query the database to pull information from different tables to perform further analysis.

The data management platforms help in managing the platforms and help in gaining insights on real- time basis, managing, storing and organizing of data.

4. Data cleaning and interpreting

One should possess a strong knowledge of data mining and advanced statistical techniques to clean and extract unstructured data.

The major motive of data cleaning is to bring accuracy and perform the task in lesser time. The professionals procure the data in bulk which is unstructured and need to be segregated in order to begin working on it.

The data professionals must possess the skill set to mine the data so that they can invest lesser time in cleaning manually and more time in productive tasks.

5. Analytical thinking and problem-solving approach

Thinking out of the box, keeping a creative mind, and having a problem-solving approach are key attributes of a good analyst. It helps you ask relevant and interesting research questions and build good repo among key stakeholders of the company.

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What are the tasks performed by Data Analysts?

By now, you would have a fair understanding of who data analysts are and what they do. Let us take a deep look into the core responsibilities that they perform on a day-to-day basis:

1. Gathering and processing data

A data analyst gathers the data from multiple sources, cleans the data, and then puts it in good shape. The collected data is used to identify trends and patterns to predict forecasts and insights. They make use of different tools to fulfil this task.

2. Identifying trends and patterns

Data analysts help in decision making, which plays a major role in the success of an organization. They translate raw and unstructured data into meaningful information to predict future forecasts, identify what went wrong in the previous quarters, and what new goals must be added for generating more sales. They should have an analytical, creative, and problem-solving mindset to provide recommendations beneficial for the business.

Preparing for a data analyst role? Sharpen your interview skills with our comprehensive list of data analyst interview questions and answers to confidently tackle any challenge thrown your way.

3. Preparing a report to record the findings

Insights found by a data analyst are useless until it is conveyed in the right context to the audience. Hence, it is the most important responsibility of a data analyst to prepare reports using a flowchart, graphs, bars, pie-charts, diagrams, tables, etc. so that people can easily consume findings. A data analyst always identifies his/her audience to prepare a report that can be understood by each decision-maker.

Check out: Data Analyst vs Data Scientist – Spot the Difference

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How should you kick-start a Career in Data Analytics?

1. Select the right role

As stated above, the data science field is very diverse, with never-ending opportunities. You must have a strong understanding of current technology trends, how data analysts drive business decisions, tools in demand, and how data science can shape the future to get a good grasp of what you do and evolve with the organization you work for.

Staying in touch with key stakeholders, top management will help you achieve the same. Do not hesitate to ask the right question to understand the different roles of a data analyst. This will help you in deciding the role that suits best to your skill set and requirements.

2. Join a Science Diploma or certification course

Understand the role that you need to perform and take appropriate guidance and mentorship from experts in this field. You must keep your skills and knowledge up-to-date with the role you need to perform. Take a step further and go for the PG diploma or certification courses to better perform your duties and strengthen your knowledge.

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3. Learn to code: choose a programming language.

You must master a programming language to become an expert in data analysis. Python and R are the most popular languages. Select the language that you are comfortable with and learn until you have good command over it.

4. Join Data Analysts community and forums

This is one of the most important steps but often overlooked. You must join a data science forum, community group, or take active participation in technical discussions to know what is happening around, how data analysis is shaping the business goals, etc.

5. Enhance your communication skills

What if you have humongous knowledge but have no idea of conveying the same to others. Watch videos or take courses to enhance your presentation and communication skills. Learn different tools to present your findings conveniently and intuitively to the key stakeholders of the organization.

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6. Focus on practical applications

Don’t just read theory, also put the knowledge to test. Start developing applications that can do your work in less time and collate data from multiple sources with less coding. You can also take a few freelancing projects to work on different datasets.

Also Read: R Developer Salary in India: For Freshers & Experienced

Conclusion

Being one of the highest-paying jobs, data analysts are in huge demand all over the world. Where the demand is going up steadily, there are not enough resources to meet the demand. This shortfall is seen across the globe. Since data plays a vital role in the success of a business, companies are in the utmost need to hire professionals who can interpret this data and put it to good use.

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This urge has led to a shift in the analyst role. With each passing day, the data analyst role is becoming more complex. Therefore, analysts must keep themselves engaged continuously in learning new tools, methods, and technology to do the task right. A good analyst with machine learning, programming language, advanced tool knowledge can rule over the ocean of Big Data and become a crucial asset for the business.

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Frequently Asked Questions (FAQs)

1. Do data analysts need to code?

Learning proper programming and coding comes under the job role of a data scientist. However, it is usual to find a data analyst with proper command over R, SQL, and Python. But, it is not mandatory to possess coding skills as data analysts work with data and prepare actionable insights from it without any coding.

2. What are some of the essential skills for data analysts?

Once you have these skills, it becomes easy to get a job in any organization for a data analyst role.

3. Do data analysts need to be good at math?

Data analysts need to move around numbers. So, one has to be proficient in math for becoming a data analyst, as it is considered the building block for this role. One has to be clear with college-level algebra and be able to deal with word problems and convert them into mathematic expressions.
Other than that, one also needs to possess a basic understanding of functions, different types of graphs, and the relationship between functions and graphs in a complete manner. At last, one needs to be well-versed with linear algebra and calculus. So, you definitely need to be good at math to become a data analyst.

4. Is data analytics a high paying job?

Yes, data analyst is a high paying job. The average salary of a data analyst is 4.3 lakhs per annum. The average salary ranges from 1.9 lakhs per annum to 11.5 lakhs per annum. The salary bracket may be differ owed to various factors such as location, skill sets, experience, education, etc.

5. Does data analyst need coding?

Yes, data analysts do require coding. The coding helps in working with data easier and smoother.

6. What is the career path of a data analyst?

The data analyst’s career path is senior data analyst, analytics manager, director, vice president or even chief data officer. All of this comes through when one keeps pushing themselves and always invest getting better than they were before.

7. Is Python required for data analyst?

The data analysts are required to work with large amount of data and excel is not the ideal choice for working with huge data sets. Rather python and other programming languages are very beneficial.

8. What skills is required for data analyst?

Some of the skills required from data analyst are mentioned below- 1) SQL 2) Python 3) R 4) Statistical literacy 5) Numeral literacy 6) Communication 7) Team management

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Computers originally created to “compute” mathematical tables could be applied to a wide range of problems across every industry – mining and machinery, transportation, hospitality, manufacturing, retail, banking & financial services, education, healthcare and Government; in the same vein, Analytics that is currently used to summarize, visualize and predict would be used in many ways that we cannot even dream of today, the same way the designers of computer systems in 60’s and 70’s could not have predicted the varied applications of computers in the subsequent decades. We are indeed in exciting times and you the budding Analytics professional could not have been more lucky. Announcing PG Diploma in Data Analytics with IIT Bangalore – To Know more about the Program Visit – PG Diploma in Data Analytics. Top Data Science Skills to Learn to upskill SL. No Top Data Science Skills to Learn 1 Data Analysis Online Courses Inferential Statistics Online Courses 2 Hypothesis Testing Online Courses Logistic Regression Online Courses 3 Linear Regression Courses Linear Algebra for Analysis Online Courses upGrad’s Exclusive Data Science Webinar for you – ODE Thought Leadership Presentation document.createElement('video'); https://cdn.upgrad.com/blog/ppt-by-ode-infinity.mp4 Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Our learners also read: Free Online Python Course for Beginners About Prof. S. Sadagopan Professor Sadagopan, currently the Director (President) of IIIT-Bangalore (a PhD granting University), has over 25 years of experience in Operations Research, Decision Theory, Multi-criteria optimization, Simulation, Enterprise computing etc. His research work has appeared in several international journals including IEEE Transactions, European J of Operational Research, J of Optimization Theory & Applications, Naval Research Logistics, Simulation and Decision Support Systems. He is a referee for several journals and serves on the editorial boards of many journals.

by Prof. S. Sadagopan

11 May'16

5.19K+

Enlarge the analytics & data science talent pool

Note: The articlewas originally written by Sameer Dhanrajani, Business Leader at Cognizant Technology Solutions. A Better Talent acquisition Framework Although many articles have been written lamenting the current talent shortage in analytics and data science, I still find that the majority of companies could improve their success by simply revamping their current talent acquisition processes. Learn data science courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. We’re all well aware that strong quantitative professionals are few and far between, so it’s in a company’s best interest to be doing everything in their power to land qualified candidates as soon as they find them. It’s a candidate’s market, with strong candidates going on and off the market lightning fast, yet many organizational processes are still slow and outdated. These sluggish procedures are not equipped to handle many candidates who are fielding multiple offers from other companies who are just as hungry (if not more so) for quantitative talent. Here are the key areas I would change to make hiring processes more competitive: Fix your salary bands – It (almost) goes without saying that if your salary offerings are outdated or aren’t competitive to the field, it will be difficult for you to get the attention of qualified candidates; stay topical with relevant compensation grids. Consider one-time bonuses – Want to make your offer compelling but can’t change the salary? Sign-on bonuses and relocation packages are also frequently used, especially near the end of the year, when a candidate is potentially walking away from an earned bonus; a sign-on bonus can help seal the deal. Be open to other forms of compensation – There are plenty of non-monetary ways to entice Quants to your company, like having the latest tools, solving challenging problems, organization-wide buy-in for analytics and more. Other things to consider could be flexible work arrangements, remote options or other unique perks. Pick up the pace – Talented analytics professionals are rare, and the chances that qualified candidates will be interviewing with multiple companies are very high. Don’t hesitate to make an offer if you find what you’re looking for at a swift pace – your competitors won’t. Court the candidate – Just as you want a candidate who stands out from the pack, a candidate wants a company that makes an effort to stand apart also. I read somewhere, a client from Chicago sent an interviewing candidate and his family pizzas from a particularly tasty restaurant in the city. I can’t say for sure that the pizza was what persuaded him to take the company’s offer, but a little old-fashioned wooing never hurts. Button up the process – Just as it helps to have an expedited process, it also works to your benefit is the process is as smooth and trouble-free as you can make it. This means hassle-free travel arrangements, on-time interviews, and quick feedback. Network – make sure that you know the best of the talent available in the market at all levels and keep in touch with them thru porfessional social sites on subtle basis as this will come handy in picking the right candidate on selective basis Redesigned Interview Process In the old days one would screen resumes and then schedule lots of 1:1’s. Typically people would ask questions aimed at assessing a candidate’s proficiency with stats, technicality, and ability to solve problems. But there were three problems with this – the interviews weren’t coordinated well enough to get a holistic view of the candidate, we were never really sure if their answers would translate to effective performance on the job, and from the perspective of the candidate it was a pretty lengthy interrogation. So, a new interview process need to be designed that is much more effective and transparent – we want to give the candidate a sense for what a day in the life of a member on the team is like, and get a read on what it would be like to work with a company. In total it takes about two days to make a decision, and there be no false positives (possibly some false negatives though), and the feedback from both the candidates and the team members has been positive. There are four steps to the process: Resume/phone screens – look for people who have experience using data to drive decisions, and some knowledge of what your company is all about. On both counts you’ll get a much deeper read later in the process; you just want to make sure that moving forward is a good use of either of both of your time. Basic data challenge – The goal here is to validate the candidate’s ability to work with data, as described in their resume. So send a few data sets to them and ask a basic question; the exercise should be easy for anyone who has experience. In-house data challenge – This is should be the meat of the interview process. Try to be as transparent about it as possible – they’ll get to see what it’s like working with you and vice versa. So have the candidate sit with the team, give them access to your data, and a broad question. They then have the day to attack the problem however they’re inclined, with the support of the people around them. Do encourage questions, have lunch with them to ease the tension, and check-in periodically to make sure they aren’t stuck on something trivial. At the end of the day, we gather a small team together and have them present their methodology and findings to you. Here, look for things like an eye for detail (did they investigate the data they’re relying upon for analysis), rigor (did they build a model and if so, are the results sound), action-oriented (what would we do with what you found), and communication skills. Read between the resume lines Intellectual curiosity is what you should discover from the project plans. It’s what gives the candidate the ability to find loopholes or outliers in data that helps crack the code to find the answers to issues like how a fraudster taps into your system or what consumer shopping behaviors should be considered when creating a new product marketing strategy. Data scientists find the opportunities that you didn’t even know were in the realm of existence for your company. They also find the needle in the haystack that is causing a kink in your business – but on an entirely monumental scale. In many instances, these are very complex algorithms and very technical findings. However, a data scientist is only as good as the person he must relay his findings to. Others within the business need to be able to understand this information and apply these insights appropriately. Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses Good data scientists can make analogies and metaphors to explain the data but not every concept can be boiled down in layman’s terms. A space rocket is not an automobile and, in the brave new world, everyone must make this paradigm shift. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on The Future of Consumer Data in an Open Data Economy document.createElement('video'); https://cdn.upgrad.com/blog/sashi-edupuganti.mp4 Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Our learners also read: Free Python Course with Certification And lastly, the data scientist you’re looking for needs to have strong business acumen. Do they know your business? Do they know what problems you’re trying to solve? And do they find opportunities that you never would have guessed or spotted?

by upGrad

14 May'16

5.69K+

UpGrad partners with Analytics Vidhya

We are happy to announce our partnership with Analytics Vidhya, a pioneer in the Data Science community. Analytics Vidhya is well known for its impressive knowledge base, be it the hackathons they organize or tools and frameworks that they help demystify. In their own words, “Analytics Vidhya is a passionate community for Analytics/Data Science professionals, and aims at bringing together influencers and learners to augment knowledge”. Explore our Popular Data Science Degrees Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Degrees We are joining hands to provide candidates of our PG Diploma in Data Analytics, an added exposure to UpGrad Industry Projects. While the program already covers multiple case studies and projects in the core curriculum, these projects with Analytics Vidhya will be optional for students to help them further hone their skills on data-driven problem-solving techniques. To further facilitate the learning, Analytics Vidhya will also be providing mentoring sessions to help our students with the approach to these projects. Our learners also read: Free Online Python Course for Beginners Top Essential Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Certifications Inferential Statistics Certifications 2 Hypothesis Testing Certifications Logistic Regression Certifications 3 Linear Regression Certifications Linear Algebra for Analysis Certifications This collaboration brings great value to the program by allowing our students to add another dimension to their resume which goes beyond the capstone projects and case studies that are already a part of the program. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Through this, we hope our students would be equipped to showcase their ability to dissect any problem statement and interpret what the model results mean for business decision making. This also helps us to differentiate UpGrad-IIITB students in the eyes of the recruiters. upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 Check out our data science training to upskill yourself

by Omkar Pradhan

09 Oct'16

5.69K+

Data Analytics Student Speak: Story of Thulasiram

When Thulasiram enrolled in the UpGrad Data Analytics program, in its first cohort, he was not very different for us, from the rest of our students in this. While we still do not and should not treat learners differently, being in the business of education – we definitely see this particular student in a different light. His sheer resilience and passion for learning shaped his success story at UpGrad. Humble beginnings Born in the small town of Chittoor, Andhra Pradesh, Thulasiram does not remember much of his childhood given that he enlisted in the Navy at a very young age of about 15 years. Right out of 10th standard, he trained for four years, acquiring a diploma in mechanical engineering. Thulasiram came from humble means. His father was the manager of a small general store and his mother a housewife. It’s difficult to dream big when leading a sheltered life with not many avenues for exposure to unconventional and exciting opportunities. But you can’t take learning out of the learner. “One thing I remember about school is our Math teacher,” reminisces Thulasiram, “He used to give us lot of puzzles to solve. I still remember one puzzle. If you take a chessboard and assume that all pawns are queens; you have to arrange them in such a way that none of the eight pawns should die. Every queen, should not affect another queen. It was a challenging task, but ultimately we did it, we solved it.” Navy & MBA At 35 years of age, Thulasiram has been in the navy for 19 years. Presently, he is an instructor at the Naval Institute of Aeronautical Technology. “I am from the navy and a lot of people don’t know that there is an aviation wing too. So, it’s like a dream; when you are a small child, you never dream of touching an aircraft, let alone maintaining it. I am very proud of doing this,” says Thulasiram on taking the initiative to upskill himself and becoming a naval-aeronautics instructor. When the system doesn’t push you, you have to take the initiative yourself. Thulasiram imbibed this attitude. He went on to enroll in an MBA program and believes that the program drastically helped improve his communication skills and plan his work better. How Can You Transition to Data Analytics? Data Analytics Like most of us, Thulasiram began hearing about the hugely popular and rapidly growing domain of data analytics all around him. Already equipped with the DNA of an avid learner and keen to pick up yet another skill, Thulasiram began researching the subject. He soon realised that this was going to be a task more rigorous and challenging than any he had faced so far. It seemed you had to be a computer God, equipped with analytical, mathematical, statistical and programming skills as prerequisites – a list that could deter even the most motivated individuals. This is where Thulsiram’s determination set him apart from most others. Despite his friends, colleagues and others that he ran the idea by, expressing apprehension and deterring him from undertaking such a program purely with his interests in mind – time was taken, difficulty level, etc. – Thulasiram, true to the spirit, decided to pursue it anyway. Referring to the crucial moment when he made the decision, he says, If it is easy, everybody will do it. So, there is no fun in doing something which everybody can do. I thought, let’s go for it. Let me push myself — challenge myself. Maybe, it will be a good challenge. Let’s go ahead and see whether I will be able to do it or not. UpGrad Having made up his mind, Thulasiram got straight down to work. After some online research, he decided that UpGrad’s Data Analytics program, offered in collaboration with IIIT-Bangalore that awarded a PG Diploma on successful completion, was the way to go. The experience, he says, has been nothing short of phenomenal. It is thrilling to pick up complex concepts like machine learning, programming, or statistics within a matter of three to four months – a feat he deems nearly impossible had the source or provider been one other than UpGrad. Our learners also read: Top Python Free Courses Favorite Elements Ask him what are the top two attractions for him in this program and, surprising us, he says deadlines! Deadlines and assignments. He feels that deadlines add the right amount of pressure he needs to push himself forward and manage time well. As far as assignments are concerned, Thulasiram’s views resonate with our own – that real-life case studies and application-based learning goes a long way. Working on such cases and seeing results is far superior to only theoretical learning. He adds, “flexibility is required because mostly only working professionals will be opting for this course. You can’t say that today you are free, because tomorrow some project may be landing in your hands. So, if there is no flexibility, it will be very difficult. With flexibility, we can plan things and maybe accordingly adjust work and family and studies,” giving the UpGrad mode of learning, yet another thumbs-up. Amongst many other great things he had to say, Thulasiram was surprised at the number of live sessions conducted with industry professionals/mentors every week. Along with the rest of his class, he particularly liked the one conducted by Mr. Anand from Gramener. Top Data Science Skills to Learn to upskill SL. No Top Data Science Skills to Learn 1 Data Analysis Online Courses Inferential Statistics Online Courses 2 Hypothesis Testing Online Courses Logistic Regression Online Courses 3 Linear Regression Courses Linear Algebra for Analysis Online Courses What Kind of Salaries do Data Scientists and Analysts Demand? Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? upGrad’s Exclusive Data Science Webinar for you – ODE Thought Leadership Presentation document.createElement('video'); https://cdn.upgrad.com/blog/ppt-by-ode-infinity.mp4 Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses “Have learned most here, only want to learn..” Interested only in learning, Thulasiram made this observation about the program – compared to his MBA or any other stage of life. He signs off calling it a game-changer and giving a strong recommendation to UpGrad’s Data Analytics program. We are truly grateful to Thulasiram and our entire student community who give us the zeal to move forward every day, with testimonials like these, and make the learning experience more authentic, engaging, and truly rewarding for each one of them. If you are curious to learn about data analytics, data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

by Apoorva Shankar

07 Dec'16