how to get data analyst job as a fresher

How to get Data Analyst Job as a Fresher?

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Data Analysis is the process of collecting, cleaning, transforming, and modeling data to extract useful information and insights. In today’s data-driven world, data analysis has become an essential skill for organizations across industries to make informed decisions and improve business outcomes. For freshers, data analysis presents an exciting career opportunity with great growth potential. In this blog post, we will explore how to get a Data Analyst job as a Fresher. Accordingly, the blog will explore the skills and tools required for a career in data analysis, the importance of building a strong educational foundation, and strategies for getting a job in data analysis as a fresher.

Key Takeaways: 

  • This demand for data analysts is driven by the increasing use of data and analytics by businesses to gain a competitive advantage.
  • According to a report by Nasscom, the Indian analytics industry is expected to grow from $2 billion in 2013 to $16 billion by 2025, at a compound annual growth rate of 26%.
  • The demand for data analysts in India is expected to reach 1.5 lakhs by the end of 2021, up from 70,000 in 2016, as per a report by Great Learning, an ed-tech platform.
  • The average Data Analyst salary in India is Rs. 4.0 lakhs per annum, according to Glassdoor.

How to Become a Data Analyst with No Experience? 

Skill development for Data Analysis

  • Technical Knowledge: Python, R, SQL, and SAS are just a few of the programming languages that a data analyst must be proficient in. A data analyst must also be skilled in Excel, Tableau, and other data visualization software.
  • Analytical skills: Data analysts must have a good eye for detail and the analytical abilities to skim across large amounts of data to find patterns, trends, and insights. Moreover, they must also be able to successfully explain their findings to stakeholders.
  • Problem-Solving Skills: Data analysts must have the ability to solve problems using a systematic and analytical attitude. Consequently, they must be able to divide complicated issues into smaller, more manageable chunks and create solutions that satisfy the requirements of their customers or companies.

Tools and technologies for Data Analysts

  • Data Management Tools: Large datasets are managed, cleaned, and manipulated by data analysts using technologies like Excel, Google Sheets, and SQL.
  • Statistical Analysis Tools: To do sophisticated statistical analysis on data sets, statistical analysis tools like R, SAS, and SPSS are utilized.
  • Data Visualization Tools: Tools such as Tableau, Power BI, and QlikView are used to create visualizations that help data analysts communicate their findings effectively to stakeholders.
  • Machine learning tools: Moreover, Predictive models for making data-driven decisions are built using machine learning tools like Python and TensorFlow.

Build a Strong Foundation

Anyone wishing to pursue a data analysis profession must have a strong educational foundation. Certainly, one needs a solid background in mathematics, statistics, and computer science to succeed in this sector. You can acquire the abilities and information necessary for data analysis through schooling, which can also make you more attractive to companies.

Courses and degrees that can prepare you to work as a data analyst include:

  • A Bachelor’s Degree: a bachelor’s degree in statistics, computer science, or a comparable discipline. You can acquire a solid foundation in mathematics, statistics, and computer science, which are necessary for data analysis, with a bachelor’s degree in a related discipline.
  • Master’s Degree in Data Science or Analytics: You can gain a more specialized education in data analysis and make yourself stand out to potential employers by earning a master’s degree in data science or analytics.
  • Certification Programs: You can obtain industry-recognized certifications and demonstrate your abilities and knowledge to potential employers by enrolling in certification programs like the SAS Certified Data Scientist, Microsoft Certified Data Analyst, and Google Analytics Certification. Additionally, you can also opt for Pickl.AI’s Data Analytics certification course that will help you become an industry expert with effective skills and hands-on experiences.
  • Bootcamps and Online Courses: Compared to traditional degree programs, bootcamps, and online courses can be more flexible and more cost-effective. Online courses and bootcamps in data analysis and related subjects are available through platforms like Udacity, Springboard, and Coursera.
  • Internships and apprenticeships: These opportunities can give you practical experience in data analysis while also advancing your career and developing your portfolio.
  • Self-Learning and Practice: These two methods can also aid in your development as a data analyst. You can learn and practice data analysis using the many resources accessible online, including books, courses, and open-source datasets.

Building a Portfolio

A portfolio is important for demonstrating your skills and expertise to potential employers. It shows that you have practical experience in data analysis and can provide evidence of your work. A portfolio can also help you stand out from other applicants who may only have academic qualifications.

A good data analysis portfolio should include projects that demonstrate your skills in data collection, cleaning, analysis, and visualization. The projects should be relevant to the job you are applying for and should showcase your ability to solve real-world problems. It should also include a description of the problem, the methodology used, and the outcome.

As a fresher, you may not have practical experience in data analysis. However, you can still build a portfolio by working on personal projects and participating in hackathons or competitions. You can also complete online courses or certification programs and showcase your skills by completing the projects provided in these courses.

Applying for Jobs

Once you have built your portfolio and acquired the necessary skills, you can start looking for job opportunities as a fresher. 

Tips on Creating a Good Resume and Cover Letter

Your cover letter and CV should involve customization for the position you’re looking for and should showcase your qualified qualifications. Make sure your resume is simple to read and includes information about your schooling, professional experience, and completed projects. Your cover letter should be clear and precise and should highlight your most important skills and accomplishments.

Getting Ready for Interviews:

To help you feel confident and prepared when you meet with potential employers, preparation for interviews is essential. You should do your homework about the business and the position, and practice interviewing with a friend or member of your family. Additionally, you should prepare answers to frequently asked questions.

Below are a few sample data analyst job interview questions:

  • Describe yourself to me.
  • What background do you have in data analysis?
  • What technology and tools have you applied to data analysis?
  • How do you deal with incomplete data?
  • How do you go about cleansing data?
  • Could you describe a data analysis project you’ve worked on for me?

Be truthful in your responses to these questions regarding your background and strategy. Focus on giving particular instances and demonstrating your problem-solving and result-achieving techniques.

What kind of companies can you hope to work for?

As a data analyst, you may opt to work for a variety of companies across different industries. Most companies today rely on data to make informed decisions, which means there is a high demand for data analysts. Here are some of the industries and companies where you can expect to find entry-level data analyst jobs with no degree:

  • Media and Entertainment
  • Consulting firms
  • Finance
  • Healthcare
  • Technology-based companies
  • Marketing
  • Education
  • Transport and Logistics

Data Analyst Salary

The compensation of a new data analyst might change depending on a number of variables. It may include region, industry, company size, and educational background. Nonetheless, the typical salary for a new data analyst in India is between INR 3-6 lakhs per year.


The compensation range for new data analysts can also change depending on their educational background. Candidates with degrees in statistics or data science may stand out from those with ordinary bachelor’s degrees.

It’s vital to remember that a data analyst’s income can rise dramatically with experience, qualifications, and extra abilities. So, for people who are interested in working with data and drawing conclusions from it, a career in data analysis can be financially rewarding.


In conclusion, becoming a data analyst as a fresher may seem like a daunting task. However, it is achievable with the right skills and approach. In this blog post, we have covered the key points to consider when pursuing a career in data analysis. It includes the importance of understanding the field and acquiring the necessary skills and tools. Additionally, it also includes building a solid educational foundation, creating a portfolio, and applying for jobs.


  • Asmita Kar

    Written by:

    I am a Senior Content Writer working with Pickl.AI. I am a passionate writer, an ardent learner and a dedicated individual. With around 3years of experience in writing, I have developed the knack of using words with a creative flow. Writing motivates me to conduct research and inspires me to intertwine words that are able to lure my audience in reading my work. My biggest motivation in life is my mother who constantly pushes me to do better in life. Apart from writing, Indian Mythology is my area of passion about which I am constantly on the path of learning more.