Data Analyst: A detailed career overview with a complete roadmap

Data Analyst A detailed career overview with a complete roadmap

As businesses today have increased their reliance on data for data-driven decision-making and providing their companies a competitive edge in today’s data-driven world, the demand for data science professionals is on the surge. Especially the role of a data analyst is becoming increasingly important to analyze the data and identify hidden patterns to assist business leaders make the right decision. Their ability to extract meaningful insights from complex datasets makes them in-demand professionals.

So, if you are looking to make a career in data science, then in this article we will have a detailed overview of the job of a data analyst; what they do, what it takes to become one, and a complete career roadmap.

Why Become a Data Analyst?

So, the first thing first. Why opt for this career path? Well, according to US Bureau of Labor Statistics, the employment of data analysts is expected to grow by 26.9% by 2032. One of the major reasons contributing to this growth is ever-increasing volume of data that needs to be analyzed to get proper insights.

A career in data analysis comes with several benefits such as:

  • Lucrative salary package: As per Indeed, the average annual salary of data analysts in the US is $77,932. The salary can go as high as $150,000 depending upon company, and experience.
  • Challenging role: the job of data analyst is not monotonous but exciting. It presents a problem-solving field where you will get to challenge your intellectual ability regularly.
  • Variety and impact: The role of data analysts isn’t confined to any particular sector. From healthcare to finance, and marketing to retail, data analysts are needed across industries. So, you will get to work on data science projects with varied domain expertise.

Roadmap to Becoming Data Analyst

1. Educational Requirements for the Role of Data Analyst

Though there is no fixed and mandatory educational requirement to becoming data analyst, having the following qualifications can significantly boost your data science career:

Bachelor’s Degree

Earning a bachelor’s degree in quantitative fields like statistics, computer science, mathematics, economics, and even business can be highly beneficial for this career path. These programs help students gain a strong foundation in analytical thinking, data manipulation skills, and programming languages like Python and SQL.

2. Learning Relevant Data Science Skills

Bootcamps and online courses

Though not mandatory, intensive bootcamps and online courses provide fast track learning platform where you can hone data science skills needed to become an efficient data analyst. In such programs you can master skills like data visualization, data analysis, wrangling, and basic programming skills. If you are looking for a quick learning option, then these can be considered, however, they do not provide in-depth knowledge as the university courses.


There are several online resources available where you can learn the basic data analysis skills by self. Platforms like Coursera, Udemy, edX, and others offer free and paid courses that you can use for your advantage.

Data Science Certifications

Data Science certifications hold immense value in the data science industry. Though not every employer asks for it mandatorily, certifications are a great way to demonstrate your data science skills and expertise and help enhance your employability along with chances of earning higher salaries. Online data science certification programs from USDSI®, Harvard, IBM, and Microsoft, are highly recognized across industries and recommend to boost your career.

3. Gain Practical Experience

Theoretical knowledge is undoubtedly important; however, employers give more weightage to practical experience of the candidates. So, you must aim to make a strong portfolio of your experience. Here are some ways to do that:

  • Internships
  • Freelancing and contract work
  • Contributing to open-source projects
  • Working on your own data science projects
  • Participate in data science competition

4. Customizing resume for specific jobs

Once you are ready with all the theoretical and practical skills and knowledge, it’s time to start the job hunt. You can tailor your resume and cover letter for the specific job you are applying for and highlight your relevant skills and experience.

5.  Network with other data science professionals

Networking with other professionals in the field can help you refer to the best job role you are seeking. Leverage professional social media platforms like LinkedIn, participate in discussions in forum, and create a place for you in the data science community.


The role of data analyst is highly rewarding and offers challenging job profile too. With the right education, skills, and planning, you can easily ace this career path. Students and professionals should also note that the data science industry is evolving rapidly with advent of newer technologies like quantum computing, AI, GenAI, etc. So, they must be prepared to upgrade themselves with the latest tools and technologies coming their way. Data science certifications can help them learn new skills and stay relevant in the market.

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