RnewGrab Deal : Flat 20% off on live classes - SCHEDULE CALL Rnew

- Data Analyst Blogs -

The Definitive Guide to Getting Started as a Data Analyst in 2023


Harvard business review rated the data analyst profession as the most excellent choice for the 21st century. The data scientist field has become one of the rapidly sought-after domains for technical aspirants and professionals. People from a variety of backgrounds are earning high salaries and getting lucrative benefits that are why they are preparing for data science. Also, people from different backgrounds are adopting this profession and getting hired by the top-most companies.

This blog is written to provide you with an idea of the career path of a data analyst, data analyst requirements, and the salary range for data scientists so that you can grasp the field and become a successful IT professional. Here, we have included a brief introduction to the career of data science and the skills required to become a data analyst along with some information on the salary structure that is being offered to these professionals by the organizations.

  • Right Skills Set Programming Mathematical
  • Earn Certifications CDMP SAS EMC
  • Why to Choose the Profession? High Demand Better Salary Evolving Field

How to Become a Data Analyst?

Here we will share an in-depth guide on how to become a data analyst. But before that, you must know who is a data analyst, data analyst requirements, data analyst prerequisites, etc.

Who Is a Data Analyst?

If you want to know why data analyst jobs are most in-demand then search on LinkedIn for the most promising jobs and your answer will be there. LinkedIn and Glassdoor like popular websites say that data analysis is one of the top jobs for many years to come. To take the data analyst job, you must have an idea of the profile and appropriate skill set as well. Moreover, to earn the major career advantages and earn fat pay packages you must acquire all possible information about the data analyst field. 

Data analyst profile is a part of the Big Data profession in which the professionals are supposed to compile and analyze statistics and information for their businesses so that they can identify the problems and suggest possible solutions. They have to also ensure data accuracy and build a database to store appropriate information. Business managers may also ask for some recommendations from them to improve the quality and efficiency of their business. Analysts have to spend many hours with computers to take out crisp information.

Why Should You Choose Data Analyst as a Profession?

Data scientists have become the most in-demand professionals and it has been declared one of the hottest jobs. The professionals have the skills and background in statistics, Math, programming, business, and other important domains. These skills help them to become perfect professionals and here we have listed the topmost reasons to become a data analyst and to join this profession:

1). Increased Demand

Global demand for skilled professionals is increasing day by day even many experts have said that the demand for skilled professionals will reach 140,000 to 180,000 in a few years. Here the supply of skilled professionals is lower than demand due to the long list of data analyst requirements, this increases the chance of getting a job and every professional is trying their luck in this field. 

As per a recent survey by Analytics Insight, by 2021, there will be over 3 million new job openings in data globally. With a projected 73% growth rate in job demand by this year, it is a perfect time to jump into the data analytics field and start learning all you can about this growing industry. Before you begin on the journey of data analyst requirements, let’s first understand the roles & responsibilities of data analysts. 

2). High Salaries

It has been seen that the average salary of data analysis professionals is INR 6,50,000 OA in India and even in the USA this is almost $1,20,931. This shows that the initial level salary is quite better for data analysts and it will become even far good for the professionals in coming years. Along with experience, the salary gets better even. Salary is another important factor apart from the increased data analyst requirements in the business. 

3). Evolving Field

Data science is supposed to be an evolving field and the demand for scientists is also increasing. As scientists have a variety of skills and can help organizations in making better decisions in a more organized way. They can get many opportunities to work with various organizations. 

Data science is part of Big Data and involves knowledge of various tools and technology. Data science has become an essential part of almost every organization, so they are hiring skilled professionals. Scientists or analysts can make the task easier and provide the information in a more organized way. And, most importantly, the path how to be a data analyst is quite straightforward. 

Data Analyst Job Profile: Top Career Options

Data analysis has become the gateway to entering the current era of automation. There are various career options in the field. Here are the top data analyst job profiles for you to go for.

  • Senior Data Analysts
  • Data Scientists
  • Data Analytics Managers
  • Business Analysts
  • Data Architect
  • Data Security Analyst

Data Analyst Roles & Responsibilities

Data analysts are mainly focused on understanding the questions the business needs to answer and finding whether those questions can be answered through data. A data analyst should be able to understand the technical issues in collecting data, analyzing data, and reporting. They must be able to recognize trends and patterns. Here are the key data analyst responsibilities:

  • Design and maintain databases by managing issues related to data.
  • Do data mining on different data sources before organizing the data in a readable format.
  • Take help from the statistical tools in predicting future trends by identifying patterns and trends in the available datasets.
  • Create and implement data analysis strategies in order to optimize the statistical quality and efficiency of the organization.
  • Design charts and reports to  build communication in the insights and make predictions from the data.
  • Create documentation to let stakeholders comprehend the entire data analysis process for future use.

Prerequisite Needed to be a Data Analyst

To pursue the DAaa Analyst Career path, you should have a four-year Bachelor's degree in either math, science, computer science, business, or statistics. However, even if you are not from this background, you can still pursue this title, provided you have a professional certificate program certification. 

To be a successful data analyst, you don’t necessarily need a high degree. But, having some knowledge of Programming Languages, Data Tools, and Statistics will certainly help you on your path to becoming an efficient professional. 

Data Analyst Salary: How Much Data Analyst Earn?

You have already know the data analyst requirements, how to get into data analytics, market demand, and the major roles & responsibilities of a Data Analyst, However, you might be wondering, ‘How much does a Data Analyst earn?,’ ‘What is the average salary of a data analyst? and so on.

 To answer these questions, yes, data analysts can earn a high payout. 

As per Indeed,  the average data analyst salary in the U.S. is $75,685. Indeed notes that data analysts can typically earn the most in non-traditional tech areas.

According to data from Robert Half’s 2021 Technology and IT Salary Guide, the average salary for data analysts depending on their experience breaks down as follows:

data analyst salary

Data analysts are among the highest-paid IT jobs. Here, the primary reason is the lack of professional’s supply and high demand due to the increasing data analyst requirements. These professionals are an extreme necessity for small as well as big corporations as most of these companies receive chunks of data on a regular basis.

Data Analyst Certification Details: Earn Big Data Certifications

There are a number of certifications available for the data scientist or data analyst profession to help you through how to be a data analyst. Which one is appropriate for you totally depends on your organizational requirement? Plenty of articles is also available that can help you in getting information about these certifications and how to be a data analyst. A certification can help you in grasping all the information and knowledge and help to prove your skills in front of the employer. The most popular certifications are

1). SAS Certified Base Programmer for SAS 9

SAS provides certifications it is considered one of the topmost credentials. This test checks the ability to import and export data from raw files along with other operations. Other operations include data manipulation, data transformation, and combining various data sets. They must have the skill to correct data and remove all programming and logical errors.

2). EMC Proven Data Analyst Professionals

These professionals are known to have all the required skills for this profession. Certification includes the questions that are relevant to data processing like cleaning or data and the use of various techniques to make it relevant and organized. EMC is the certification that helps the professionals in becoming the relevant ones and supports their questions on how to be a data analyst.

3). CDMP or Certified Data Management Professional

This is authorized by non-profit organizations like DAMA or Data Management International Association. In this certification, there are four credentials for the professional that are associate, practitioner, master, and fellow level. The candidates with 6-month experience can become associate-level professionals and must have strong knowledge of DMBOK principles. 

The candidates with more than 5 years of experience can become CDMP professionals and after 10 years they can become the data management professional practitioner and apply for the master CDMP this is how to get into data analytics. CDMP fellows have extensive experience in the data management field and can become proven speakers, publishers, workshop presenters, and other similar ones.

Skills Required to Become Data Analyst in the Talent Market

The rewards of a data analytics job do come without significant training and effort. The data analyst requirements include specific skills and tech central qualifications in terms of data analyst education requirements. This is also to keep in mind when it comes to what to study to become a data analyst. In addition, you also need to have a handful of soft skills. 

There is not a single way to gain all the skills required to become a data analyst. While some opt into master’s programs, a growing cohort of learners has begun enrolling in short-term data science courses. But regardless of the route, you decide to choose, you will need to acquire a sturdy set of skills in order to become an in-demand data professional and this is how to become a data analyst: 

Technical Skills Required to Become Data Analyst

When it comes to the data analyst prerequisites, the candidate should have a well-developed toolbox of technical skills. Here are a few to focus on: 

Learn Programming

As far as popular and most used programming skills required for the data analyst profession is concerned then mostly R and Python are used by data analysts. Learn machine learning languages if you want to be a perfect data analyst. As far as machine learning languages are concerned then you must know supervised, unsupervised, and reinforced learning. You must be familiar with the below-listed concepts if you want to be a perfect data analyst and looking for how to get into data analytics:

  • Linear and Logical Regression
  • Random Forest
  • Clustering
  • Decision Tree
  • K Nearest Neighbor

Do Read Important Interview Questions on Data Structures!

Deep learning is also recommended for machine learning professionals and is among the top data analyst prerequisites. You must know the below-listed concepts of deep learning if you want to become a perfect machine learning experience:

  • Neural Network Fundamentals
  • Tensor flow or Keras-like deep learning libraries so that a perfect learning model can be generated.
  • Understand how Recurrent, Convolutional Neural network, Autoencoders.

Learn the Data Visualization

Data visualization is also imperative in the data processing life-cycle and among the must-have data analytics prerequisites. Even it also requires a good knowledge of data processing tools.  Few tools are listed below that may be required and used by the professionals:

  • Tableau
  • Google Charts
  • Data wrapper
  • Kibana 

Having knowledge of these tools can make you a perfect and efficient data analyst. It is basically a person’s ability to display data finding through graphics or other illustrations. The purpose is to facilitate a better understanding of data-driven insights. Data visualization helps data professionals help businesses in decision-making. 

Master the Big Data Skills

Big data is almost everywhere and is required by almost all data science professionals, Today, every organization wants to collect and store all data that is present across social networking sites and throughout the internet. They do not want to miss out on any information that may be of their use. Today huge data is floating around all over the internet it may be beneficial in various ways for organizations. Even the use of this data depends totally on the organizational requirement. 

Big data is in the frontiers of the IT field and it makes the process of decision making and business conduction easier. It has become a crucial part of every organization and can provide cutting-edge solutions for complicated organizational issues. So, data analysts must also know about Big data frameworks like Spark or Hadoop and it is one of the data analytics prerequisites. 

Learn Data Ingestion and Data Munging

Data ingestion means importing, transferring, process, and loading the data to and from the database. Here data loading and sourcing can be performed from various sources. Here are many tools used for this process like

Read: 23 Smart Data Analytics Tools For Perfect Data Management

  • Apache Sqoop
  • Apache Flume

Having knowledge of these tools is one of the requirements for a data analyst.


Python is one of the most important data analyst requirements. This is a high-level general-purpose programming language that offers a remarkable number of specialized libraries, many of which pertain specifically to AI. Understanding Python is a skills data analysts must keep current in the AI-concerned professional landscape. 


One of the most well-used languages when looking for how to be a data analyst, R is used in analytical work. It encompasses various built-in, easy-to-use data organization commands by default. This language also appeals to businesses since it can easily handle complex and large quantities of data. No doubt, it is on the top list of data analyst requirements.


One of the requirements for a data analyst is SQL. SQL persists as the standard means for querying and handling data in relational databases. The branded versions of SQL like MySQL come up with opportunities to gain a better understanding of relational database management systems and is one of the data analytics prerequisites. The NoSQL framework effectively structures its information in any way if the available method is not relational. 

Machine Learning

Learning ML helps you become competitive in the data analytics industry and perfectly fits with the data analytics requirements. While you may not be working on machine learning projects, having a general understanding of the tools and concepts provides you with an edge over competitors and this is how to become data analyst.  

Before applying the data analytical models, data analysts have to perform feature selection also. This is a part of making raw data clean that involves many steps. The complete process to make raw data clean is known as data munging. R and Python packages can also be used for this purpose. It is one of the most important parts of the data life cycle. 

Being a data analyst or scientist, you must know which feature is important and must be there in the package, along with the information on the features that must not be part of your package. Any data inconsistency must be removed. This is the task and steps for data munging.

If you are fresher and fixed between whether to pursue business analyst or data analyst, here's a guide for you on – Business analyst vs Data analyst

Soft Skills Required to Become Data Analyst

Here are the major soft skills every data analyst should have to shine in the industry:

1). Attention to Detail

To make yourself aligned with the data analyst requirements, you must have the ability to notice every minor detail. You should be able to notice the small clues pointed toward a larger message. The skills come in handy when data analysts work on building processes to capture and sort data. A single error in the code can affect the whole workflow awry. 

2). Critical Thinking

Data analysts are responsible for uncovering and synthesizing connections that are not very clear. Here, you should be able to think analytically about data, find patterns and extract actionable insights. It is one of the vital data analyst requirements to go above and beyond and apply yourself to thinking, as opposed to only processing. 

Having excellent communication skills, problem-solving, research and team management are some of the major data analyst requirements one needs to have to shine in the career. 

Steps to Become a Data Analyst

Steps to Become a Data Analyst

A good data analyst must have the above skills to perform his tasks. Below is the step-wise process on how to become data analyst –

Step 1: Check the Educational Requirements

When you are looking for a data analyst education requirements, having knowledge of Science, Technology, Engineering, and Mathematics is considered the best starting point to get the basic skills. However, an undergraduate or a postgraduate degree in a relevant discipline such as Computer science, Economics, IT, and Mathematics is vital for becoming a data analyst. 

Step 2: Focus on Learning Programming

To become a data analyst, you should have some level of coding knowledge and experience. You need to have the knowledge of SQL, and basic Python skills and master the key libraries required for this role, including Pandas, Matplotlib, Seaborn, Numpy, and Scikit Learn.

Step 3: Take A Data Analysis Course

In the next step, consider taking up a data analysis course to gain the most required data analysis skills. These certification courses are meant to provide you with a comprehensive overview of the subject in a shorter period. There are numerous short-term and long data analysis course options that you can choose at your convenience.

Step 4: Apply for Jobs & Interview Preparation

After you have finished your certification training course, it’s time to showcase your qualification and knowledge and land your dream job. Don’t forget to update your CV and portfolio before applying for the job openings. Prepare for the interview to give your best and you are all set to fly. Here are some of the top 30 Data Analyst Interview Questions and answers. 

The role of a data analyst is very high-paying. If you want to become a data analyst without having any prior experience then you should strengthen your basics of data analysis first, take up some data analysis projects and build your profile. Some project work experience and some added skills would make your data analyst resume stand out and can help you land your dream job.

Here are the tips for becoming a data analyst and getting lucrative salary packages:

So, if you are passionate about data, statistics, and algebraic functions then just shape your career and grasp all the required skills on becoming a data analyst. The below-listed skills are required to be a data analyst:

  • Basic SQL skills
  • Pattern finding and matching ability
  • Some knowledge of development skills
  • Ability to find actionable insights from processed data
  • Knowledge and experience in Microsoft Excel

In the end, we can say that data analyst requirements involve higher mathematics and statistics. The job involves both software development and programming.

Looking for a career in data but confused between data science and data analyst, this comprehensive guide on data science vs data analyst might help you to take the right decision! 

Last Verdicts on Data Analyst Requirements

With the mentioned salary range, and increasing market demand, it is clear that the data analyst job is very lucrative and high-paying. If you fulfill the basic data analyst requirements, you can explore data analytics jobs in all sorts of industries, and there’s more than one path toward securing your first job in this high-demand field. Whether you’re just getting started in the professional world or pivoting to a new career, data analysis is an ideal career option. And, this is how to become data analyst. 

If you are confused about what to study to become a data analyst? You can begin your journey towards becoming a data analyst by getting a free consultation from your subject matter experts at JanBask Training. We will guide you on what skills to work on your skills and learn data analysis from the scratch!.

Do connect with us by sharing your experiences if you have been successful in this field. Till then, happy learning!

Frequently Asked Questions on Data Analyst Requirements

Q1). How to become a data analyst without any prior experience? 

Ans:- Here is a quick guide on how to become a data analyst when you are a fresher:

  • Check for the data analyst education requirements
  • Begin with Self-Study
  • Work on Data Analytics Projects 
  • Create a strong Portfolio
  • Apply for Internships and entry-level jobs

Q2). What is the difference between a Business analyst vs data analyst?

Ans:- In the  Business analyst vs Data analyst, business analysts work on the data to help organizations make effective business decisions. While data analysts are mainly involved in gathering and analyzing data for the business to evaluate and use to make decisions on their own. 

Q3). What to study to become a data analyst? 

Ans:- In the data analyst requirements, having a high degree is not mandatory. But you can begin with a bachelor's degree and apply for most entry-level jobs. Generally, data analysts hold degrees in fields like mathematics, finance, statistics, economics, or computer science. In addition, strong math and analysis skills are needed.

Q4). What is the difference between Data science vs data analyst? 

Ans:- Data analysts mainly work through the existing data, whereas a data scientist works on new ways of capturing and analyzing data to be used by the analysts. This is the only difference in data science vs data analyst otherwise, both job profiles are focused on numbers, statistics as well as computer programming.

Q5). How long does it take to become a data analyst?

Ans:- Well, there is no fixed rule on how long does it take to become a data analyst, generally, data analyst positions need a bachelor's degree that typically takes around 3-4 years to finish. A master's degree or MBA can be done in under two years, and a post-mas ter certificate can be completed in under a year.

 Q). How to prepare for the data analyst job interview? 

Ans:- The preparation for the interview begins with showcasing your skills. Build your portfolio, highlighting your data analysis skills during the conversation. Then, prepare to answer the Data analyst interview questions. Practice answering interview questions and completing take-home assessments. 

Q7). How to learn data analytics on my own? 

Ans:-Once you decide to become an expert professional in data analysis, you can begin anywhere and start working on data analyst requirements. First, choose a Programming Language, dive into learning the Advanced Technical Topics, practice with tools, and try to level up your soft skills. This is how to learn data analytics. 

Q8). How to get a data analyst job without any prior experience? 

Ans:-If you have the relevant knowledge, you can kickstart your preparation for becoming a data analyst without any previous experience Strengthen your basics of data analysis and begin applying for data analysis internships and entry-level jobs and this is how to get a job as a data analyst. 

Q9). How to get a job as a data analyst without a degree? 

Ans:-There are not a lot of data analyst requirements, as you don't need a full-blown degree. Focus on following a structured and formal approach to learning the required skills and getting hands-on experience on how to get a job as a data analyst. 

So, are you ready to take the next career step in data analysis? Examine your work environment, and experience, and go for a Data Analytics training course. Hopefully, you found this guide helpful. 

Feel free to share if you have any doubts or questions relevant to Data Analyst requirements or how to get a data analyst job we will get back to you soon with answers.

fbicons FaceBook twitterTwitter google+Google+ lingedinLinkedIn pinterest Pinterest emailEmail


    Puja Bhardwaj

    This is Puja Bhardwaj, a creative writer, and content strategist. I’m passionate about storytelling through written and visual content, and market that content for cultivating a committed audience. I come to the table with 5 years of content writing and marketing experience (in the agency, in-house, and freelance writing).


  • J

    Jaden Hernandez

    Thank you for this post. I really like all this information and tips. Wish you all the best!

    • Puja  User


      Glad to hear that you found this post valuable. Often visit our website to read more such posts.

  • E

    Emerson King

    Great article with so many job options. I will share it with my friends who are looking to create their career in the tech field but have no technical degree. I hope this will help them.

  • R

    Ronan Wright

    Outstanding article. You have smoothly covered so many career options available for those who do not have any degree. Thanks a lot for sharing it!

    • Puja  User


      We are happy to hear that you have gone through the post so deeply.

  • K

    Karson Lopez

    This post has every job option one can have without a degree. This is really awesome. Thanks for sharing!

    • Puja  User


      Our focus has always been to provide something valuable. Glad, you found it helpful.

  • A

    Arlo Hill

    It is really nice to see how smoothly you have covered all the major jobs options without making it boring. Heads Up to you!

    • Puja  User


      Thank you so much for these motivating words, we are glad to hear them from you.

  • T

    Tobias Scott

    No doubt, this is a complete guide on creating a career without any degree. Thank you so much for sharing it.

  • B

    Brady Green

    I was not very aware of so many career options available without a degree. It is really very helpful for those who are looking for jobs and do not have any degree. Thanks a lot for sharing!

  • C

    Clayton Adams

    I just passed out from my college and am trying to land a good job. The blog post is well-scripted like your other posts.

    • Puja  User


      It’s our pleasure that you find our post valuable. We will keep trying to bring more and more interesting and informative content.

  • C

    Caden Thomas

    The web is full of articles and videos on creating a fulfilling and bright career. But the way this post is planned and written is really awesome. Thanks for sharing!

    • Puja  User


      This is quite motivating to hear from you, keep visiting our site to read such posts.

  • J

    Jax Williams

    I have been following your blog posts for a long time and learning something interesting every time. This time also, I could explore a lot about the career related to different domains.

    • Puja  User


      You could learn something new from our post, this is really good to hear.

Trending Courses

AWS Course


  • AWS & Fundamentals of Linux
  • Amazon Simple Storage Service
  • Elastic Compute Cloud
  • Databases Overview & Amazon Route 53
AWS Course

Upcoming Class

2 days 08 Jun 2023

DevOps Course


  • Intro to DevOps
  • GIT and Maven
  • Jenkins & Ansible
  • Docker and Cloud Computing
DevOps Course

Upcoming Class

1 day 07 Jun 2023

Data Science Course

Data Science

  • Data Science Introduction
  • Hadoop and Spark Overview
  • Python & Intro to R Programming
  • Machine Learning
Data Science Course

Upcoming Class

3 days 09 Jun 2023

Hadoop Course


  • Architecture, HDFS & MapReduce
  • Unix Shell & Apache Pig Installation
  • HIVE Installation & User-Defined Functions
  • SQOOP & Hbase Installation
Hadoop Course

Upcoming Class

3 days 09 Jun 2023

Salesforce Course


  • Salesforce Configuration Introduction
  • Security & Automation Process
  • Sales & Service Cloud
  • Apex Programming, SOQL & SOSL
Salesforce Course

Upcoming Class

3 days 09 Jun 2023

QA Course


  • Introduction and Software Testing
  • Software Test Life Cycle
  • Automation Testing and API Testing
  • Selenium framework development using Testing
QA Course

Upcoming Class

-1 day 05 Jun 2023

Business Analyst  Course

Business Analyst

  • BA & Stakeholders Overview
  • BPMN, Requirement Elicitation
  • BA Tools & Design Documents
  • Enterprise Analysis, Agile & Scrum
Business Analyst  Course

Upcoming Class

3 days 09 Jun 2023

MS SQL Server Course

MS SQL Server

  • Introduction & Database Query
  • Programming, Indexes & System Functions
  • SSIS Package Development Procedures
  • SSRS Report Design
MS SQL Server Course

Upcoming Class

3 days 09 Jun 2023

Python Course


  • Features of Python
  • Python Editors and IDEs
  • Data types and Variables
  • Python File Operation
Python Course

Upcoming Class

17 days 23 Jun 2023

Artificial Intelligence  Course

Artificial Intelligence

  • Components of AI
  • Categories of Machine Learning
  • Recurrent Neural Networks
  • Recurrent Neural Networks
Artificial Intelligence  Course

Upcoming Class

11 days 17 Jun 2023

Machine Learning Course

Machine Learning

  • Introduction to Machine Learning & Python
  • Machine Learning: Supervised Learning
  • Machine Learning: Unsupervised Learning
Machine Learning Course

Upcoming Class

24 days 30 Jun 2023

Tableau Course


  • Introduction to Tableau Desktop
  • Data Transformation Methods
  • Configuring tableau server
  • Integration with R & Hadoop
Tableau Course

Upcoming Class

3 days 09 Jun 2023

Search Posts


Receive Latest Materials and Offers on Data Analyst Course