Businesses rely on data insights to guide their decision-making, and because of this business environment of today places a high value on data analysis. Since there is a growing need for qualified data analysts, more people are considering pursuing careers in this area. A job in data analysis might be intimidating, especially for individuals without any expertise in the industry. The good news is that you don't need any experience to become a data analyst. This post will discuss how to become a data analyst with no experience in detail.

Can Someone Who Has Never Had Experience Become a Data Analyst?

Yes, it is feasible to work as a data analyst without having any prior experience. People can develop the skills and knowledge they need to be successful in this industry if they put in the effort, are open to learning, and have access to the correct training resources.

How to Become a Data Analyst With No Experience?

Becoming a data analyst without prior experience can be a challenging but achievable goal. It requires a combination of self-directed learning, skill development, networking, and strategic job searching. Here’s a detailed guide on how to break into the field of data analysis from scratch:

1. Understand the Role and Responsibilities

Before embarking on this journey, it's crucial to understand what data analysts do. They interpret data and turn it into information that can offer ways to improve a business, thus affecting business decisions. They gather information from various sources and analyze patterns, trends, and correlations.

2. Acquire the Necessary Skills

Data analysts need a mix of technical and soft skills. Start by learning the basics of:

  • Statistics and Mathematics: Understanding the fundamentals of statistics and mathematics is crucial for analyzing data effectively.
  • Programming Languages: Python and R are the most common programming languages in data analysis for data manipulation and statistical analysis.
  • Data Visualization and Reporting: Tools like Tableau, Power BI, or even Excel for creating dashboards and reports that can communicate your findings.
  • SQL and Databases: Knowledge of SQL is essential for querying databases to extract and manipulate data.
  • Microsoft Excel: A powerful tool for basic data analysis, familiarize yourself with advanced formulas, pivot tables, and data visualization features.

3. Work on Personal Projects or Volunteering

Applying your new skills to real-world problems is a great way to gain experience. You can start with personal projects like analyzing public datasets, participating in Kaggle competitions, or volunteering your data analysis services to non-profits or small businesses.

4. Build a Portfolio

Create a portfolio to showcase your projects and analyses. This can be a GitHub repository, a personal blog, or a website where you share your projects, insights, and methodologies. Your portfolio should demonstrate your ability to extract meaningful insights from data and your proficiency with the tools and techniques of data analysis.

5. Networking and Mentorship

Connect with professionals in the field through LinkedIn, local meetups, or professional associations. Look for a mentor who can provide guidance, feedback on your projects, and potentially help with job referrals. Networking can be invaluable in learning about unadvertised job openings or internships.

6. Gain Formal Education

While not strictly necessary, having a degree related to data science, computer science, statistics, or a related field can be beneficial. Alternatively, consider certification programs specifically designed for data analytics, which can also add value to your resume.

7. Apply for Entry-Level Positions or Internships

Look for job titles like "Junior Data Analyst," "Data Technician," or "Analytics Assistant." Tailor your resume to highlight your analytical skills, projects, and any relevant coursework or certifications. Even customer service or administrative roles that involve data entry or reporting can serve as stepping stones, giving you practical experience with data.

8. Prepare for Interviews

Be ready to discuss your projects, how you approached problems, and what you learned. You should also be prepared for technical interviews that may test your knowledge of statistics, programming, and data analysis techniques.

9. Continuous Learning and Professional Development

The field of data analysis is constantly evolving, so it’s important to keep learning new tools, technologies, and methodologies. Join forums, attend workshops, and continue taking courses to stay current with industry trends and advancements.

What Is Data Analytics?

To learn about data analysis, you must first know what data analytics is. The term "data analytics" refers to a group of quantitative and qualitative methods for drawing important conclusions from data. To extract numerous patterns, interactions, connections, and other significant insights from it, data science entails several steps, including gathering data and classifying it.

What Do Data Analysts Do?

On huge datasets, data analysts gather, analyze, and run statistical studies to glean insights and spot trends. They use various methods and tools to transform complicated data into useful insights. They, therefore, provide insightful data that enables businesses to make informed decisions, and this answers the question of what data analysts do.

Roles and Responsibilities of a Data Analyst

The roles and responsibilities of a data analyst often consist of the following:

  • Create and manage databases and data systems, fixing coding mistakes and other data-related problems as necessary.
  • Using both primary and secondary sources for data mining.
  • Rearranging data in a way that both individuals and machines can understand. 
  • Create documentation that clarifies the data analysis process for stakeholders.

Entry Level Data Analyst Salary

Your amount of experience is one of the most important aspects that could influence your pay. Data analysts may often anticipate making more money the longer they work in the field. But the entry-level data analyst salary could be $59,730.

Entry-Level Data Analyst Jobs You Can Get Without Experience

Without prior experience, you can work as a Data Entry Analyst, Junior Data Analyst, Marketing Data Analyst, Operations Data Analyst, Sales Data Analyst, or Healthcare Data Analyst. Strong analytical skills, meticulousness, and familiarity with data management systems are frequent requirements for these positions. Your chances of landing an entry-level data analyst position might be improved by gaining experience through internships or side projects.


It is possible to become a data analyst without prior experience if you have the correct attitude, commitment, and strategy. You may acquire the skills and knowledge required to succeed in this fascinating subject by following the instructions in this post. However, there is always an opportunity for improvement and learning in data analysis, so enrolling in a thorough data analysis course can provide you with the groundwork and resources you need to further your career.


1. Is coding required to become a data analyst?

Although it might not be necessary for data analysis tasks, having coding knowledge might still be a big help in finishing the job.

2. What credentials do I need to be a data analyst?

Any degree in computer-related specialization can help you to become a data analyst.

3. Can anyone pursue a career as a data analyst?

Anyone with the necessary skills and the determination to pursue it may achieve their goal of becoming a data analyst.

4. To become a data analyst, how many years are needed?

It can take anywhere between a year and four years for someone with little to no experience who wants to become a data analyst to complete their certification or degree and acquire the necessary skills.

5. Are data analysts in high demand?

Given the high need for data analytics, the employment prognosis for data analysts is highly favorable.

Data Science & Business Analytics Courses Duration and Fees

Data Science & Business Analytics programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Post Graduate Program in Data Engineering

Cohort Starts: 16 Jul, 2024

8 Months$ 3,850
Applied AI & Data Science

Cohort Starts: 16 Jul, 2024

3 Months$ 2,624
Data Analytics Bootcamp

Cohort Starts: 23 Jul, 2024

6 Months$ 8,500
Post Graduate Program in Data Analytics

Cohort Starts: 1 Aug, 2024

8 Months$ 3,500
Post Graduate Program in Data Science

Cohort Starts: 7 Aug, 2024

11 Months$ 3,800
Caltech Post Graduate Program in Data Science

Cohort Starts: 7 Aug, 2024

11 Months$ 4,500
Data Scientist11 Months$ 1,449
Data Analyst11 Months$ 1,449

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