How To Become A Data Analyst: A Step-by-Step Guide

April 23rd, 2024
How To Become A Data Analyst

With the rise in data generation, data analysts have become highly sought-after professionals globally. These are the ones who enable organizations to solve complex problems and make data-driven decisions. They play a crucial role in many leading industries, which has led everyone to ask how to become a data analyst.

This article has tapped into a few other imperative questions that usually people ask along this key question. Here is everything needed to get on with a career in this expanding field of data analytics.

Explore igmGuru Power BI training program to become a successful data analyst.

Who Is A Data Analyst?

So, who is a data analyst? A data analyst is a data expert with the skills and knowledge to extract valuable insights from gigantic data sets. They follow a set procedure to help businesses drive growth via informed decision making. These include data collection, processing and performing statistical analysis.

Every leading industry today seeks the aid of these experts for market research, logistics and translating sales figures- all in English. The findings are made usable through their efforts in regulating, calibrating and normalizing the data. 

Why Start A Career As A Data Analyst?

With so many people searching how to become a data analyst, it becomes important to also answer why start a career as a data analyst.

  • Growing Role Demand 

Data analytics is a field that is enjoying a rapidly expanding market size, which is expected to reach $303.4 billion USD in 2030. This means the demand will grow at an even more rapid pace than today.

  • High Data Analyst Salary 

A data analyst salary is around $77.5k USD per year on an average. In India, a data analyst earns somewhere around Rs.6 LPA on an average. This is on the intermediate level, with salaries going way higher with more experience and expertise.

  • Domain Flexibility 

These experts can easily find a job in different domains like marketing, finance, healthcare, etc.

Types of Data Analysts

types of data analysts

Based on the skill set and interests, it is possible to pursue several different types of data analysts roles. Some of the most common ones are-

  • Business Analysts- They collect, analyze & interpret complex sets of data to aid organizations in making informed data-decisions. They closely work with stakeholders.
  • Data Scientists- They design and develop complex algorithms to find solutions to different problems. They employ advanced analytical techniques to uncover valuable insights.
  • Financial Analysts- They enable organizations to make financial decisions by analyzing related data like profitability, expenses and revenue. 
  • Healthcare Analyst- They enable healthcare organizations to enhance patient outcomes while limiting the costs. They analyze clinical trials, insurance claims and patient records.

You May Also Read- Data Analytics Tutorial for Beginners: A Step-By-Step Guide

How To Become A Data Analyst

Still wondering how to become a data analyst? These pointers will certainly help!

1. Fulfill Data Analyst Qualifications and Prerequisites

The first thing certainly is to fulfill data analyst qualifications and prerequisites.

  • Qualification- A bachelor's degree in computer science, IT, statistics, economics, mathematics or engineering. A master's degree is required in certain companies.
  • Programming Languages- Python and R are common programming languages for data analysis. Their libraries and adaptability are used for data analysis and manipulation.
  • Mathematics & Statistics- In-depth knowledge of concepts like calculus, linear algebra, inferential statistics and probability is imperative.
  • Database Skills- To work with gigantic data sets, knowledge of SQL and databases is essential.

2. Gain Technical Skills

  • Data Visualization- Master key data visualization techniques by employing tools like Seaborn, Matplotlib and ggplot2. This aids creating informative and meaningful charts, visual representation and graphs.
  • Machine Learning Basics- Machine learning basics are needed to understand more about applying classification and predictive models.
  • Statistical Analysis- Statistical techniques like descriptive statistics, regression analysis and hypothesis testing are applied to draw valuable insights.
  • Data Cleaning & Manipulation- Learn processes involved in cleaning, preprocessing and transforming data.
  • Critical Thinking & Problem Solving- Strong critical thinking and analytical skills are needed to work with complex problems.

3. Take a Data Analyst Training

A data analyst training program is the key to becoming a professional. Learning under the guidance of industry experts will ensure acquiring all necessary key skills and information. An online program is a great way to get started since this saves a lot of time associated with an offline program.

Self-paced programs are also getting a lot of attention these days. It is apt for anyone who wants to get the same learning experience as an instructor-led program, but without being bound to attend the classes.

4. Gain Practical Experience

Gaining practical experience is imperative to open doors to top organizations since most hiring managers lay focus on this factor. There are two ways to make it happen.

  • Projects- Working on data analysis projects is a great way to showcase skills to those taking the interview. Adding this to the resume showcases the interviewees ability to deal with real-world problems and issues.
  • Entry-Level Positions/ Internships- To gain actual-world knowledge, an internship or an entry-level position is a great option. Both will actually ensure great learnings.

5. Start Networking

There are many ways to begin networking with like-minded people such as workshops, meetups, events and communities. Connect with professionals in the same field, having different knowledge and expertise. Networking is one of the best ways to open job prospects and learning opportunities.


Data application is becoming wider and more indispensable in most industries today. This has led to a steep rise in the demand for certified, qualified and trained professionals with experience and expertise.

This blog has paved a path on how to become a data analyst, along with the reasons to get started in this field. Get certified with a leading credential like Google Data Analytics Professional Certification or AWS Certified Data Analytics to get access to top jobs globally.

FAQs For How To Become A Data Analyst

Question 1. Is it hard to study data analysis?

Studying data analysis requires good knowledge of data manipulation, mathematics, statistics and programming. Hence, it's not exactly a piece of cake, but certainly a rewarding one.

Question 2. Is data analyst a lot of math?

Data analysts must be adept in using numbers and have a good grasp over statistics and math.

Question 3. Can a fresher become a Data Analyst?

It is possible to get started as a fresher by going for entry-level jobs or completing associated internships.

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