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Information is the oil of the 21st century, and analytics is the combustion engine.
-Peter Sondergaard
You might have heard of the famous brand 'Coca-Cola'.
Do you know that data is changing the way Coca-Cola approaches its marketing strategies?
Yes. It has leveraged data to its advantage in decision-making and conducting experiments.
For example, it uses data gathered from consumer feedback to come up with new products.
How?
Coca-Cola has internally connected vending machines all across the world. These machines allow customers to create their own drinks.
Through this, they can see some real trends and patterns, especially by countries and regions, which are then aggregated over time.
These findings are then used to come up with completely new product ideas, like 'cherry-flavoured Sprite' or 'Exotic mango-flavoured diet coke'.
It sounds fascinating, right?
This is precisely what Data Analytics is, with, of course, multiple layers included.
In today's world, data is everywhere. Businesses are collecting more data than ever before, and they are looking for ways to use this data to their advantage.
If you love problem-solving and have a knack for details, then being a Data Analyst might be your calling.
In this blog post, we're going to explore what it means to be a Data Analyst, why it's a great career choice, and how you can become one.
Data Analysts collect, analyse, and interpret data to help businesses make better decisions. For this, they use a variety of tools and techniques.
They then use this information to identify trends, patterns, and insights that can be used to improve business performance.
Whether it's determining the most profitable product, identifying the latest market trends, or predicting future sales, a Data Analyst holds the key to unlocking the value in data.
In this section, we will look at the process followed by a Data Analyst within an organisation to come up with reliable findings that eventually form the foundation of the decision-making process.
This includes stages such as:
Data Analyst: A person who is better at statistics than any software engineer and better at software engineering than any statistician.
1. Foundational Knowledge
It's not mandatory to have a background in Mathematics, Statistics, Economics, or Computer Science.
BrainStation's most recent Digital Skills Survey reported that 76 percent of respondents did not begin their career in data, and nearly two-thirds have been working in the field for only five years or less.
However, it is important to develop a solid understanding of Math, Statistics, and Problem-solving.
2. Data-Analytics Certification
Though you don't need a full-fledged degree in this field to embark on a career, a structured and formal approach to acquiring the necessary skills makes the process easier for you.
Here is a list of things you should look for before choosing a course:
3. Learn relevant tools
Programming languages like Python and SQL and knowledge of data visualisation tools like Excel, Tableau, etc. are non-negotiables and must be mastered from the very beginning.
4. Industry-relevant Projects
Getting hands-on experience with real-time data-oriented problems will not just give you an opportunity to test your acquired skills but will also enhance the credibility of your resume or portfolio, making you more employable.
Getting internships or working as a freelancer can give you the much-required industry exposure.
5. Develop soft skills
The responsibilities of a Data Analyst aren’t just confined to analysing data but also presenting the findings to all the stakeholders.
For this, you need to have soft skills like communication, problem-solving, decision-making, etc., which will not just help you with showcasing your functional findings but also help in maintaining healthy professional relationships, which will make you an asset to the company in the long run.
6. Networking
Reaching out to people from your own field makes you open to different perspectives and broadens your horizons. It can also help you identify a mentor, thus keeping yourself on track not just during the tenure of your course but throughout your career as well.
7. Start Applying for Jobs
Once you feel confident that you have acquired the necessary skills and have worked on a sufficient number of projects, start applying for jobs.
Use notable job portals like LinkedIn, Naukri, Indeed, etc to find data analyst Jobs. The professional network you built and the mentor you reached out to can also be used to expose you to relevant job opportunities.
Keep shyness at bay and make the most of every platform you have.
8. Lifelong Learning
This isn't the last step, but a tendency you should build as early as possible and carry on for the rest of your life.
As this field is extremely dynamic, there’s no reaching an ‘I-know-it-all’ stage but constant upgradation with new tools and techniques that enter the scenario, thus keeping yourself relevant amidst changing times.
It will not just make you more employable but also accelerate your growth in your current organisation.
Getting sceptical regarding the stability of any field is quite obvious, especially in the current scenario of mass layoffs and rapid integration of AI.
Fortunately, the job outlook for Data Analysts is bright.
Although some aspects of the work may be automated, substantial growth in Data Analytics jobs has been predicted.
Data Analytics as a field is omnipresent in all industries, from healthcare and transportation to manufacturing and banking. With a massive increase in the amount of data generated, the demand for professionals who can derive meaningful insights from it is ever-increasing.
To begin with, the global data analytics market size is projected to grow from $7.03 billion in 2023 to $303.4 billion in 2030 at a CAGR of 27.6%.
Moreover, acquiring Data Analytics skills paves the way to other career paths, including information security, market research, management, computer systems, and financial analytics. These all fall under the top 25 careers according to U.S. 2023 News’s Best Jobs Ranking.
On top of that, advancements in fields like AI and Machine Learning are opening up new avenues for data professionals. So, whether you choose to remain a Data Analyst or decide to climb up to more advanced roles, the future looks promising.
For example, Data Analytics opens the door to Data Science, another credible career path with an excellent job outlook.
Now you might wonder, What about the Indian Market?
According to the India Brand Equity Foundation, the Data Analytics industry in India is expected to reach a market value of up to 9.87 lakh crore INR and create over 1 crore jobs by 2026.
Apart from traditional sectors like IT and finance, even sectors like agriculture, entertainment, and education are embracing data analytics. This means a wider job market for data professionals.
Furthermore, with the concept of remote work becoming more acceptable, Indian Data Analysts also have opportunities to work for overseas companies, giving a significant boost to their job prospects.
In short, the job outlook for Data Analysts in India is glowing. The opportunities are vast, the growth is substantial, and the future is bright.
Now let’s take a look at the diverse job profiles an individual can enjoy after acquiring the skills of a Data Analyst. Some of these job profiles include:
They are the key player in any data-driven decision-making process. They clean, process, and interpret data to help companies make better decisions.
Data Analyst salaries in India range from ₹ 1.7 lakhs to ₹ 11.1 lakhs, with an average annual salary of ₹ 4.1 Lakhs. Salary estimates are based on the 83.7k latest salaries received from Data Analysts.
A more specialised role where the analyst uses data to solve business-related problems, optimise operations, and improve strategies.
Business Analyst salaries in India range from ₹ 2.7 lakhs to ₹ 15.0 lakhs, with an average annual salary of ₹ 6.6 Lakhs. Salary estimates are based on the latest 110.9k salaries received from Business Analysts.
These analysts work specifically with marketing data to help create targeted advertising campaigns and improve customer relations.
Market Analyst salaries in India range from ₹ 2.0 lakhs to ₹ 13.7 lakhs, with an average annual salary of ₹ 6.0 Lakhs. Salary estimates are based on the latest 2.5k salaries received from Market Analysts.
They focus on the internal processes of a company, using data to streamline operations and increase efficiency.
Operations Analyst salaries in India range from ₹ 2.4 lakhs to ₹ 8.0 lakhs, with an average annual salary of ₹ 4.0 Lakhs. Salary estimates are based on the latest 11.5k salaries received from Operations Analysts.
These professionals use data to analyse financial markets and guide investment decisions.
A financial analyst’s salary in India ranges between ₹ 2.0 lakhs and ₹ 11.0 lakhs, with an average annual salary of ₹ 4.0 Lakhs. Salary estimates are based on the latest 50k salaries received from Financial Analysts.
Reaching the end of this guide, we hope that you now see a clear path towards becoming a Data Analyst. It's an exciting journey, filled with lots of learning and the chance to have a great job in the world of data.
Every successful Data Analyst started just like you, curious and eager to learn. So, don't worry if the list of skills seems lengthy or the time to learn feels too stretched. With focus, curiosity, and the right help, you can master this field.
Not sure where to start or how to build the right skills to become a Data Analyst?
Don't worry, we've got your back.
Join the NxtWave Intensive Program. Learn directly from alumni of IITs and industry experts from top MNCs such as Microsoft and Amazon to become an in-demand Data Analyst.
Some of the key highlights include:
The NxtWave Intensive program has proven to be successful in guiding aspiring developers to build a solid foundation, master essential skills, and secure their dream jobs as Data Analysts.
Over 1000 of NxtWave learners with zero coding knowledge from various educational backgrounds have achieved software jobs. Check out the inspiring success stories of our learners here.
No, while having a background in Mathematics or Statistics can certainly help, it's not a must. Many Data Analysts come from different academic backgrounds and learn the necessary skills through online courses, boot camps, and self-study.
Yes, familiarity with programming languages like Python or R is important for a Data Analyst. These languages help in data cleaning, data manipulation, and data visualisation.
The time frame varies depending on your background and the amount of time you can dedicate to learning new skills. With NxtWave's Intensive Program, you can expect to be job-ready within 5 to 8 months.
Absolutely! Many people transition into data analytics from different fields. You just need to acquire the right set of skills. This is where NxtWave's Intensive Program comes in handy.
Yes, the demand for Data Analysts in India and around the world is high and is expected to grow in the coming years due to the increased use of data in decision-making processes within organisations.
As of 2023, the average salary of a Data Analyst in India is between INR 3 - 6 LPA for beginners. With experience and advanced skills, the pay can go much higher.
While both work with large amounts of data, the key difference lies in what they do with it. A Data Analyst often explains past and present business scenarios by interpreting data. A Data Scientist, on the other hand, uses data to predict future outcomes and trends.
