Anand KumariMarch 5, 2023

How to Become a Data Analyst


In search of their vocation, which will bring a good income, many become acquainted with previously unfamiliar professions. This article will talk about data analytics, the importance of this job, and all the features that are important and useful to know before you go deep into this field. 

What is a Data Analyst?

Before describing the profession itself, it is important to understand the meaning of the term "data analytics." Data analytics is a lot of information that is taken as a tool and collected in an automatic and not only automatic way. The term consists of mathematical statistics, and tables, lists, and special programs are often used to structure the resulting data. 


A data analyst is a person who collects a huge amount of information, but that's not his only task. Skills are necessary because they need to process the information and summarize the results. The result of data collection is very important for businesses, so they often hire such analysts to help them better understand the number of visits, where more potential customers come from, etc. 


A data analyst helps a business better understand its characteristics and see points of development. An experienced and competent specialist is a sought-after individual, whose work is the basis for important and weighty decisions in companies. In addition, analysts appear not only in business but also in many other life stories. For example, they help ordinary people by analyzing information about road closures, and traffic jams, through the use of drones from Tesla or other companies that collect such data. 

How to Become a Data Analyst with no experience?

A beginner, with desire and a positive attitude as well as patience, can get started in this field by learning some important topics. It is worth starting with mathematical statistics and probability theory, as well as SQL. It is not necessary to start with very complex tasks, but rather to learn to focus on simply formulated problems. 


After the basic materials, you should move on to familiarizing yourself with the Python libraries. You can't do without structuring a lot of data, so go through the video tutorials and practically master Excel, which consists of extensive functionality. 


There are some tips from experts who have been down the novice path. Use the following tips to get off to a successful start in your data analytics career:

  • Research this market, including job sites. This will help you understand what is relevant now and what skills customers require. 

To form a certain impression and notion, it is necessary not just to review a large number of jobs, but to analyze them.  This will help familiarize you with the fact that analysts come in different forms: marketing, Power BI analyst, Web analyst, etc. 

  • Get motivated. 

This is a general rule that is relevant in any profession. Motivation is an important part of the road to success. Ignite that feeling by reviewing successful people and following analysts who are leading the way. 

  • Start gaining practical experience while you're learning. 

These can be internships. Here it is important to focus not on the salary, but on the development of skills. Look for an option that can teach you something. 

  • Create a portfolio. 

The portfolio is a business card of the specialist, the main purpose of which is to attract customers. It consists of your best work and should have the right structure and design. Reviews from satisfied clients will be an additional advantage. If you have taken courses, be sure to add a document proving your qualifications. 

  • Decide what kind of analyst you want to be and research what requirements for data analyst jobs are then needed.

Analysts can be different, so it is worth starting with the one that is closer to you and more to your liking. For example, a standard data analyst helps a business collect and analyze information. An analyst in marketplaces works with marketplace data to determine which points are working and increase efficiency. Also meet analysts in e-commerce, product, marketing, web analytics, BI - analyst, and FinTech analyst.

Requirements to be a Data Analyst

There are common myths about skills, so dubious sources should not be trusted. To be proficient, you need to have both hard and soft skills. 


Let's start with the hard skills, which include an understanding of the work with tools such as SQL (getting the necessary information from different databases and the ability to carry out their primary processing). Python is used for pre-processing and modeling. Then, the findings and results are formalized with special schemes, tables, and graphs in systems that are called BI. BI systems are a way to enter the world of customers (businesses and managers), because with these tools they perceive the information more conveniently, because it is presented in a systematically correct and visually comprehensible form. Hard Skills should also include Excel and Microsoft Office. These tools are responsible for solving problems quickly and communicating in simple language between two parties. 


Soft Skills include skills that are just as important. The analyst must conventionally move to the side of the customer and understand his needs, his desires. This will allow you to cope with your tasks more effectively and not do unnecessary work. Giving results will be the ability to communicate, ask the right questions and communicate with the owners or manager of a particular business. The data analyst must be able to match business and development objectives. Correct hypothesis formulation is an important skill that must be exercised before proceeding with the job. 


If we talk about programming languages, there are several. Improve each one and learn a new one as you grow. Let's list the programming languages with which the future data analyst will have to get acquainted:

  1. SQL
  2. Python
  3. R. 
  4. Java
  5. C++.
  6. Scala. 
  7. Julia. 

In fact, there are many more programming languages. Each is characterized by its own characteristics and performs a list of specific tasks. You can only understand them better in practice. When using different programming languages, the specialist will feel the advantages and it will allow him to get the right balance. 

How to become a Data Analyst without a degree?

To give a single answer to the question "how to become a big data analyst and what prerequisite will be" is impossible because each specialist has his own path, which he makes on the basis of his characteristics and abilities. To get a decent wage and work in this field does not have to graduate from high school. It is enough to have a great desire, and patience, to start studying and choose the right courses. There are many of them, so we will highlight a few options:


- Data Analyst with R


- Data Analyst with Python


- Become a Data Analyst


- Data Analysis: Statistical Modeling and Computation in Applications


- Data Analyst by IBM


- Google Data Analytics


- Introduction to Data Analytics

On the Internet, anyone can read and get a lot of information about this profession and more. But it is not given out for free in the amount needed. The use of proven courses will allow a more effective start and even save time, thanks to the absence of unnecessary information that is not useful in the work. In addition, some training resources along with courses provide guarantees and help you find your first clients. This may not be a direct transfer of customer contacts, but training on how to communicate with potential clients, how to offer your services, present yourself in the form of a portfolio, etc. 


There are both online and offline courses, so future professionals have the right to choose how they feel most comfortable. Study the reviews and recommendations so that you don't make a wrong choice and check the level of expertise of the person who is the creator of such courses. 


Additionally, you can study literature. For example, concerning communication, because there is a lot of information and the whole range of usefulness does not always fit into one course. In addition, practice shows that literature really has a positive effect on the development of thinking, so many successful people in different fields are constantly engaged in reading. 

How to become a Data Analyst after 12th?

Data analysts are in demand in various sectors of the economy, so their popularity is only increasing every year. In connection with this, there is a growing shortage of specialists. New analysts are also emerging thanks to universities with a specialization in this department. If you want to get a degree and higher education based in this field, go to a university. This is possible if you have graduated from high school (college) and received a high school education, and if you have met all the conditions that are put forward individually by a particular institution. 


If you want to become a data analyst, you should look at these universities in India:

  • IIM Calcutta.

This is one of the most prestigious schools in the country, so the knowledge will be appropriate. During the training, you will learn all the important tools and at the end, you will be able to call yourself an analyst with confidence. 

  • Goa Institute of Management.

Students at this university receive a diploma and the opportunity to continue working in the field of science. After training, you can become a big data analyst and earn good money. 

  • The Presidency University of Bangalore.

You have to prepare for your studies in advance because the university aims to produce the best specialists. Not everyone can enter, but only those who successfully pass the interview stage. 

  • SRM Institute of Science and Technology.

It is a private institute that operates a rich program in the field of analytics. To get in, you have to pass the entrance exam and fit the rules. After that, you have to study for 4 years in order to receive a bachelor's degree. 

  • Indian Institute of Science. 

This university covers all material that is related to the analyst profession and offers an interdisciplinary program of study. 


Choose your training responsibly, because it's what lays the foundation. Whether you choose a university or a course, approach this stage responsibly, weighing the pros and cons and learning the ins and outs of each option. 

The benefits of working as an analyst

First of all, to work in this field, you have to be willing to work with numbers, because in most cases they reflect the data best. Let us note the advantages that characterize this profession:

  • The opportunity to train anyone who wants to.

In today's reality, anyone can become a data analyst in a short period of time. It is enough to show a desire and to find the appropriate training (university, courses, teacher, or self-study). A degree in mathematics is not a prerequisite for the job, although it is an advantage. On average, it takes one year to become a specialist. 

  • Decent and stable income. 

Data analysts are a profession that falls under IT specialties, so they are highly paid and valued. There are many tasks and offers, so the market needs specialists. A newcomer in the beginning can take on the most difficult and paid tasks to gain experience. Then, he can find regular customers who will provide him with a stable job, and, accordingly, a steady income. 

  • Demanding.
  • A wide range of specializations. 

Above we have already listed what kinds of analysts. In the process of work or training, everyone can choose the most suitable and liked option, and continue to develop in this direction. 

  • Communication with different businesses, including large companies. 

As a specialist grows, he gets the opportunity to work with larger customers, which is an advantage because it gives additional knowledge, acquaintances, and motivation. 

  • Work from anywhere in the world. 

Analysts have the opportunity to work for themselves and take on as many assignments as they can seamlessly handle. This is a type of remote work when the place is not important, the main thing is to have a computer and the Internet.

  • Fast career growth. 

Here much depends on the specialist, his skills, desire, etc. If an analyst works in a company, he can start with the simplest position, and then gradually rise to a senior analyst, and later even to the head of the department. 

  • Work in a team.

If you start working for a company, you will be surrounded by other employees of different levels, ages, etc. They are a good influence on professionals who are just beginning their careers because they can give advice and share experiences. 


It is worth noting that this profession is responsible and requires constant concentration. The analyst increases his or her mental tension while working, as it is necessary to perform tasks effectively. You will notice more advantages and peculiarities in practice because some things are subjective and are perceived differently by each specialist. 

Frequently asked questions (FAQ)


What qualifications do I need to be a data analyst?


To become a data analyst, you typically need a bachelor's degree in a field such as mathematics, statistics, economics, computer science, or information management. Strong analytical and technical skills, particularly in areas such as SQL, programming, and data visualization, are also important. Some employers may also require experience working with large datasets and knowledge of statistical analysis methods. Additionally, effective communication and interpersonal skills are necessary to communicate findings and insights to stakeholders.


How do I start my career as a data analyst?


To start a career as a data analyst, you can follow these steps:


Acquire education: Earn a bachelor's degree in a relevant field such as mathematics, statistics, computer science, economics, or information management.


Gain experience: Participate in internships, volunteer work, or independent projects to build a portfolio of your skills and knowledge.


Build technical skills: Learn programming languages such as SQL, Python, and R. Familiarize yourself with data visualization tools like Tableau or PowerBI.


Network: Attend industry events and connect with other professionals in your field to expand your network and stay informed about new trends and technologies.


Keep learning: Stay up-to-date with advancements in the field by taking online courses, attending workshops and conferences, and reading industry publications.


Apply for jobs: Apply for entry-level data analyst positions, tailor your resume and cover letter to highlight your relevant skills and experience, and prepare for job interviews.


Remember, starting a career as a data analyst requires dedication and hard work, but with persistence and continuous learning, you can achieve your goal.


Can I become a data analyst in 3 months?


Becoming a data analyst in just 3 months is challenging and unlikely, as it requires a solid foundation of education, experience, and technical skills. However, you can make significant progress towards your goal in that time by taking steps such as:


Learning the basics: Start by familiarizing yourself with the foundational concepts of data analysis, including statistics, programming, and database management.


Building technical skills: Take online courses or tutorials to learn programming languages such as SQL, Python, and R, and data visualization tools like Tableau or PowerBI.


Practicing: Work on real-world projects, either independently or through online platforms, to gain hands-on experience and build a portfolio of your work.


Networking: Attend industry events, connect with other professionals in the field, and join online forums to learn from others and expand your network.


It's important to remember that while you can make significant progress in three months, becoming a fully qualified and experienced data analyst typically takes years of dedicated effort and learning.


Is it hard to become a data analyst?


Becoming a data analyst can be challenging, but it is not impossible. It requires a strong foundation of technical skills, including proficiency in programming languages such as SQL, Python, and R, as well as data visualization tools like Tableau or PowerBI. Additionally, it requires a solid understanding of statistics and the ability to apply statistical analysis methods to real-world problems.


To become a successful data analyst, it's also important to have strong critical thinking and problem-solving skills, as well as effective communication and interpersonal skills to clearly articulate insights and findings to stakeholders.


However, with dedication and hard work, anyone can develop the skills and knowledge needed to become a data analyst. By taking courses, working on projects, networking with others in the field, and staying up-to-date with industry developments, you can build the foundation you need to pursue a career in this exciting field.