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How to Become a Data Analyst (With or Without Experience)

How to Become a Data Analyst (With or Without Experience)

Data is the world’s largest commodity, and in today’s digital era, every business wants to make use of it to improve their products and services. According to Enterprise Today, businesses that use data analytics to drive their business decisions are 77% likely to succeed. That’s why every business, be it startups or top MNCs, across various sectors like finance, healthcare, banking, manufacturing, or government background, is focusing on data analytics.

According to LinkedIn, the market value for Data Analytics at the beginning of 2023 stood at US$31 billion and is predicted to reach $115 billion USD by 2028. That means over the course of the next 4 years, the data analytics market will grow by almost 4 times.

Feeling intrigued? If you’re, then keep on reading further! In this article on how to become a data analyst, we are going to cover the roadmap that will help you establish a career as a Data Analyst.

Table of Contents:

Check out this interesting video on How to become a Data Analyst in 2024:

Who is a Data Analyst?

In the current age of the digital economy, everything is driven by data. From market research and product design decisions to supply chain management, everything relies on the data. However, most business owners or stakeholders struggle to understand the insights hidden in data. The raw data might seem daunting and confusing to them.

That’s where the role of a data analyst comes into play. They convert the raw data into visually appealing dashboards, by highlighting important insights that were hidden inside the data. Data analysts further break down those insights for stakeholders and business owners, to help them make better business decisions.

Types of Data Analyst – How to Become a Data Analyst – Intellipaat

A data analyst can be given different titles based on their expertise and the industry, as follows:

  1. Business Analyst
  2. Financial Analyst
  3. Marketing Analyst
  4. Social Media Analyst
  5. Business Intelligence Analyst
  6. Healthcare Data Analyst
  7. Data Scientists

Moving on, before we understand how to become a data analyst, we will try to understand why one should prefer a career in the field of data analytics.

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Why Become a Data Analyst?

The data analytics industry is growing at a rapid rate. The US Bureau of Labor Statistics states that the demand for data analysts will increase by 23% year-on-year from 2021 to 2031. What that means is that in the coming years, there are going to be a lot of employment opportunities.

Why Become a Data Analyst – How to Become a Data Analyst – Intellipaat

Source: US Bureau of Labor Statistics

Besides, since the day generative AI came into play, people have understood that data-related jobs are the future. Searches for “how to become a data analyst” have grown immensely. The Economic Times has predicted that by 2026, there will be 11.5 million additional data related jobs available globally, so this is encouraging for aspiring professionals.

One more thing to note is that, when you compare all the data science job roles, a career in data analytics is the easiest of them all. You just have to learn the skill to understand data and gauge insights out of it. 

So if you’re looking for an easier data job role with vast career opportunities, data analytics is the right call for you.

Data Science IITM Pravartak

Data Analyst Job Description

Data analysts study data from different sources, like sales records, market surveys, logistics, and user behavior. They make sure the data is accurate using their technical skills. Then, they analyze and share insights to help individuals, businesses, and groups make decisions by understanding, showing, and explaining the information.

We went through a couple of data analyst job descriptions available on the LinkedIn job-board. Here’s how the job description for Genpact looks like:

Data Analyst Job Description Genpact – How to Become a Data Analyst – Intellipaat

Source: Genpact Data Analyst Job Description LinkedIn

The data analyst job description for JPMorgan Chase & Co.:

Data Analyst Job Description JPMorgan Chase & Co. – How to Become a Data Analyst – Intellipaat

Source: JPMorgan Chase & Co Data Analyst Job Description LinkedIn

After going through multiple job postings, we figured that data analyst job descriptions may change from industry to industry or even company to company. But certain responsibilities remain the same. Here are the common and critical responsibilities data analysts take on:

  • Acquisition of data from primary or secondary data sources
  • Interpretation of data and exploratory data analysis
  • Analyzing local, national, and global trends that might impact business
  • Understanding KPIs and delivering actionable insights
  • Creating and maintaining rich interactive visualizations
  • Maintaining database
  • Sound knowledge of SQL, Excel, PowerBI, or Tableau
  • Preparing reports for higher management and stakeholders to help them make better decisions

Skills Required to Become a Data Analyst

Skills Required to Become a Data Analyst – How to Become a Data Analyst – Intellipaat

As we discussed at the time, a data analyst is responsible for analyzing the data and coming up with insights that will help stakeholders make better decisions. In order to do the analysis, here are the skills every data analyst must possess:

  • Sound knowledge of Python & R
  • Proficiency  in SQL and Data Scraping
  • Familiarity with NoSQL
  • Experience with spreadsheets
  • Hands-on Tableau and Power BI expertise
  • Basic understanding of Data Cleaning and Data Visualization
  • Mastery in Machine Learning
  • Skills in creating presentation

How to Become a Data Analyst: Step-by-Step Roadmap

Step-by-Step Roadmap to Become a Data Analyst – How to Become a Data Analyst – Intellipaat

Following this detailed roadmap helps you gain the skills to succeed as a data analyst, opening up many professional opportunities in this exciting field:

Step 1: Have a Relevant Degree

Most recruiters, if they were to hire you as a data analyst, would like to see evidence of your educational background in data analytics itself. There are various ways to get this done. You can opt for a bachelor’s degree in data analytics, or you can go for an exhaustive online data analytics bootcamp.

If you go for a B.Tech. degree, you would require 4 years of extensive learning. But, if you’re already from a bachelor’s background in BCA or BSc, then you can go for a master’s degree like M.Tech, MCA, or any other. However, the cost associated with this route will be quite substantial. 

Bootcamp is a much more cost-saving option. And if you’re working professionally, you will be able to learn data analytics, while not losing out on your monthly paychecks.

Step 2: Sharpen your Analytical Skills

When it comes to beginning a data analysis learning journey, most often you will receive a recommendation about getting started with mathematics and statistics. While it’s true that to be able to deal with data, you need the ability to deal with numbers, having a solid mathematical foundation would definitely help. Even without much statistical knowledge, pursuing a career in data analysis is still achievable and exciting.

You can learn the art of data analytics with some dedication, practice and imply hands-on approach based mode of learning. Remember, there will be hard times, you will be stuck, might even feel demotivated, but you should just keep at it.

Join the forums to get your queries resolved. Try to visualize the data-scenario as a problem, and analytically try to pose a solution. In order to do that, first follow the following segments: 

  • Start with understanding basic data and statistics terminologies, including probability distributions and hypothesis testing.
  • Try working on spreadsheets, learn about exploratory data analysis by cleaning and loading data over there. 

So, by doing this would act as a positive beginning to your learning journey.

Step 3: Mastery in Programming Languages

The third step involves mastering programming languages like Python or R, which unlock powerful tools for data analysis. Proficiency in these languages helps you clean data, construct predictive models, and automate repetitive tasks. Start by developing expertise in essential frameworks and libraries like NumPy, Pandas, Matplotlib, Scikit-learn (Python), and Tidyverse (R). These tools serve as an essential toolkit, not only for streamlining the data analysis process but also for empowering you to dive deeper into the data.

Step 4: Proficiency in Database Management

Developing proficiency in database management and SQL (Structured Query Language) is another crucial step. This empowers data analysts to efficiently retrieve and process data from databases.
Begin by solidifying your understanding of fundamental database management and SQL concepts. Simultaneously, engage in regular practice on platforms like HackerRank and LeetCode. This dual approach establishes a strong foundation and takes you towards proficiency.

Step 5: Craft your Data Visualization Skills

Unveiling insights through compelling visualizations is a crucial step for any data analyst. Start exploring powerful tools like Tableau, Power BI, or Matplotlib / Seaborn (Python) to transform your data into visually appealing charts and graphs. 

Consider diving into online courses to grasp the fundamentals of each tool. Installing them on your system at the same time as you start using them can help you become more confident and solidify your skills.

Step 6: Take on Real-World Projects

Now that you’ve mastered some of the essential skills, start working on some real-world projects on your own. Real-world projects are incredibly important for landing a job as a data analyst. They bridge the gap between theory and practice, showcase your skills, develop critical thinking and problem-solving, and gain industry experience. Above all, they help you build your portfolio as a data analyst.

And to work on real-world projects, you need to find the relevant data to explore. For this, there are various online platforms that you can refer to like:

  • Kaggle – A community platform for data science discovery and collaboration that includes datasets, contests, and tools.
  • UCI Machine Learning Repository – A large repository of standard datasets for experimentation and research in machine learning.
  • FiveThirtyEight – A website that focuses on data-driven journalism and provides public datasets for analysis, frequently with a political or social scientific theme.

Step 7: Create Data Analyst Resume & Profiles Over the Job-Boards

Make your resume relevant to the job role:

  • Go to job posting sites such as Naukri or LinkedIn and look for data analyst positions.
  • Carefully read the responsibilities and note down important keywords mentioned in job descriptions.
  • Naturally weave these relevant keywords into your resume, ensuring your skills and experience align with the specific requirements. This strategy makes your resume more noticeable to Applicant Tracking Systems (ATS).

Network and build your online presence:

  • Create or update your profiles on popular job boards such as LinkedIn and Naukri.
  • Make sure to frequently update your profiles with your relevant skills and accomplishments.
  • Actively engage on these platforms by sharing your achievements, progress, and industry insights. By doing this, you become more visible to recruiters and have a better chance of getting interviews.

Step 8: Prepare for Data Analyst Interviews

Reviewing mathematical and statistical principles is a good place to start when getting ready for a data analyst interview. Next, become familiar with standard data analysis methods, resources, and programming languages, including R, Python, and SQL. To help with interview preparation, practice some of the frequently asked questions for this position and participate in mock interviews at the same time. 

Investigate the company you are applying to in-depth before making any of these arrangements. Discover the goals and principles of the business as well as the goods and services that are available. Explore the roles and responsibilities associated with the position of a data analyst within that company.

Prepare yourself for the industry by going through these Data Analyst Interview Questions now!

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How to Get a Data Analyst Job with No Experience?

So, if you are thinking about how you can get a data analyst job without any experience – then you are not alone. Yes, it will be a bit of a challenging journey for sure, but it’s not impossible. 

Start your learning journey by building statistical intuition. Then you can go for easier tools like Excel, which you are already familiar with. Once you understand Excel, it will be easy for you to learn tools like Tableau and Power BI. Later, you can deep dive into critical data analytics skills, such as Python, R, EDA, Machine learning, etc.

Remember, every data analyst has gone through this learning phase. If they have done it, you can too. All you need is the ability to keep learning. There are plenty of learning resources available, such as free blogs, YouTube videos, and well-tailored training programs. If you follow the proper learning schedule, you will be able to become a data analyst.

Data Analyst Jobs

Right now, if you go over to the search engine and search data analytics jobs available in India, you will find out that on just the LinkedIn job-board there are 1,02,000+ jobs available. Whereas if you search for data analytics jobs in the USA, you will find out that there are 1,74,000+ jobs available.

Data Analyst Jobs in India – How to Become a Data Analyst – Intellipaat

Source: Data Analyst Jobs India LinkedIn

Data Analyst Jobs in USA - How to Become a Data Analyst - Intellipaat

Source: Data Analyst Jobs USA LinkedIn

And this is just LinkedIn. Considering other job boards such as Naukri.com or Indeed, the numbers would be even larger. That is why you should understand how to become a data analyst and start your preparation right away!

Read our blog on Data Analyst Roles and Responsibilities for more details.

Data Analyst Salary

Explore the attractive salary packages for data analysts in India and the US, highlighting their importance across the global job market, as follows:

Data Analyst Salary in India

According to Glassdoor, the salary for Jr. Data Analysts in India ranges from ₹6 lakh to ₹8 lakh per annum. Certainly, with experience, the salary could go as high as ₹18 lakh per annum.

Data Analyst Salary in India – How to Become a Data Analyst – Intellipaat

Source: Data Analyst Salary India Glassdoor

Data Analyst Salary in USA

According to Glassdoor, the salary for Jr. Data Analysts in the USA ranges from US$85,000 to US$100,000 per annum.  Furthermore, with experience, the salary could go as high as US$150,000 per annum.

Data Analyst Salary in USA – How to Become a Data Analyst – Intellipaat

Source: Data Analyst Salary USA Glassdoor

Conclusion

If you want a stable career, a data analyst position is a great choice. Due to the increasing demand for data, businesses will need someone to collect, process, and interpret it. You’ll be in charge of helping companies interpret their data so they can make wise decisions. If you have the required education and work experience, you can have a prosperous and protracted career in this field.

Data Analyst FAQs

What is required to become a data analyst?

The very first thing you need is a bachelor’s degree in a relevant field like computer science, statistics, mathematics, finance, or economics. If you don’t have it, then professional certification is preferred. You will also require strong data analytics skills, such as SQL, data visualization, proficiency in Python and R, Power BI or Tableau, Excel, etc. Additionally, a strong aptitude for working with numbers is crucial.

Can a fresher become a data analyst?

Yes, any fresher can start their career as a data analyst without any prior experience by obtaining the necessary qualifications and skill sets, which are required for a data analyst role.

Is Python required for data analysts?

For a data analyst, a comprehensive grasp of Python programming is a must. It allows the development of models, the automation of repetitive processes, and the execution of intricate analyses.

How long will it take to become a data analyst?

It takes 3-6 months of dedicated learning to gain basic proficiency in data analytics, but achieving mastery in data analytics typically takes three to four years. This initial proficiency can be gained by focusing on fundamental tools, techniques, and programming skills relevant to data analysis.

Is data analyst a lot of math?

A solid foundation in mathematics is necessary for success in data analysis, just like in any scientific field. Prior to studying how to become a data analyst, you may need to examine and, if necessary, improve your math skills.

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About the Author

Principal Data Scientist

Meet Akash, a Principal Data Scientist who worked as a Supply Chain professional with expertise in demand planning, inventory management, and network optimization. With a master’s degree from IIT Kanpur, his areas of interest include machine learning and operations research.