Do you have a question How to Get a Data Analyst Job in 2024? First of all, Congratulation! You have chosen a profitable, secure, and most demanding career. But if you are confused How to Get a Data Analyst Job? then don’t worry. I am here to clear your doubts and guide you on a clear path. I have written this article for both people- who have no experience as well as who have experience. So, give your few minutes and get a clear answer to How to Get a Data Analyst Job?
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In this blog, I am gonna tell you-
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How to Get a Data Analyst Job in 2024?
So, you have chosen the Data Analyst field. It’s a great Decision. But getting a job as a Data Analyst requires some skills. These skills are Technical skills as well as business skills.
I am here to give you complete knowledge in Data Analyst field. So, let’s start with the definition of a Data Analyst. And then we will move forward to the Roles and Responsibilities of a Data Analyst.
What is a Data Analyst?
As the name suggests, “Data Analyst“, that means a person who analyzes the data. Data Analyst is a person who collects the data, cleans that data, analyze the data, and represent the valuable findings from that data in a visual form.
In a nutshell, a Data Analyst converts numbers into plain English. A Data Analyst delivers the value to the company by finding valuable insights from the data.
You will understand more about Data Analyst by its Roles and Responsibilities. So, let’s see the Roles and Responsibilities of Data Analyst-
Roles and Responsibilities of Data Analyst
Data Analyst performs these jobs on a daily basis-
- Collecting Data and Interpreting Data.
- Data Cleaning, a data analyst clean the data. Cleaning requires removing noise from the data. The collected data contains noise, so data analysts clean the data before analysis.
- Data Analysts find out important insights from a huge amount of data. This is the main role of the Data Analyst. There are various programming languages are available for Data Analysis like Python, R, and SaaS.
- Data Analysts also finds out the Trends and Patterns from Data. Data Analysts look for short-term as well as long-term trends for the company. Trend Analysis helps Data Analyst to find business strategies for their company.
- Another important role of the Data Analyst is creating data reports and visualization of patterns with the help of various reporting tools. Data reports made by Data Analyst helps business executives to make better business decisions.
- Visualization of data is also part of a Data Analyst. Data Analysts use catchy graphs and charts to visualize their findings.
- A data analyst writes SQL queries for data extraction from the Data warehouse.
So, these are Roles and responsibilities of the Data Analyst. As you are planning to enter into the Data Analytics field, you might have a question in your mind, ” Is Data Analyst a Good career or not?.” So, let’s see whether its a good career or not.
Is Data Analyst a Good Career in 2024?
In short, answer is Yes. Let me explain why.
Today’s age is of the Data age, where lots of data is generated daily. One single Facebook “like” also generates data. So, you can imagine how much data is generated daily. But this huge data is useless without a Data Analyst.
This huge amount of data contains various useful information that can help the industry. So to find out useful information from a huge amount of data, Data Analyst comes into the picture.
That’s why there is a huge demand for Data Analysts. But the supply is not that much. And this is the reason for the High salary in this field. This is happening globally and is not restricted to any part of geography.
So, if you are planning to become a Data Analyst, then you are on the right path. Data Analyst is definitely a good career. And it’s scope is not going down in the future.
As I discussed High salary, now you may be thinking How much Data Analyst earn?. So let’s see in the next section-
How much Data Analyst Earn?
The salary of Data Analyst depends upon the Experience level. So, let’s break down into two parts-
1. Salary for Freshers/ Entry Level Data Analyst
In India, the salary of entry-level Data Analyst ranges from INR 174,667 to 753,908/ year. It includes Bonus and Profit sharing.
In the USA, the salary of entry-level Data Analysts ranges from $ 36,993 to $ 79,400/ year. It includes Bonus and Profit sharing.
2. Salary for Experienced Data Analyst
In India, the salary of experienced Data Analyst ranges from INR 372,184 to 20 Lakh/ year. It includes Bonus and Profit sharing.
In the USA, the salary of experienced Data Analysts ranges from $ 40,831 to $ 101,273 / year. It includes Bonus and Profit sharing.
Now, you have a clear idea about Data Analyst job roles, salary, now you may be thinking. “How I get a job as a Data Analyst?”
So, don’t worry. In the next section, I will explain the complete career path to become a Data Analyst.
Data Analyst Career Path
The career path to becoming a Data Analyst is a bit different for Freshers and Experienced people. In this article, I will discuss both cases- career path for fresher and for experienced.
So, let’s start the career path for freshers. If you are an experienced guy, you can skip this section.
Data Analyst Career Path for Fresher in 2024
I am going to discuss all the requirements for getting an entry-level data analyst job. So, the first and most important requirement is your Qualification.
Qualification Required
- You should have a Bachelor’s degree in Computer Science/ IT, Economics, Statistics, or Mathematics.
So, if you have a Bachelor’s degree in any of these fields, then congratulations, you are one step closer to become a Data Analyst. If you have not, then it’s better to first earn a Bachelor’s degree in any of these fields.
Now, the next step is gain some mandatory skills for Data Analyst. So, let’s see what skills are required to become a Data Analyst?
Skills Required
In order to become a Data Analyst, you should have Technical Skills as well as some business skills. So, let’s start with Technical skills-
Technical Skills
You should have following Technical skills in order to become a Data Analyst-
1. Programming-
Programming knowledge is a must-have skill for a Data Analyst. This is the core skill that makes Data analyst apart from Business Analyst. You must have a knowledge of one or more programming languages like Python, R, or SaaS. Along with that, you should be familiar with data science libraries and packages (such as ggplot2, reshape2, NumPy, pandas, and scipy).
Knowledge of all programming languages is not required. You can choose any language.
Now, you may be thinking where to learn these languages?. So, don’t worry, I have chosen some best resources for you.
Where to learn Programming?
For Python
- Python for Everybody (Coursera)– This is one of the Best Online Courses available for Python Beginners. Approximately 1.6M students have been enrolled in this course. You can check out this course here-Python for Everybody.
- The Python Bible™ | Everything You Need to Program in Python (Udemy)– This is another best course available for Python Beginners. You can check the course details here.
For R
- R Programming A-Z™: R For Data Science With Real Exercises! (Udemy)– This course is for complete Beginners in R. After completing this course, you will have complete knowledge of R Programming. You can check the course details here.
- Data Science: Foundations using R Specialization (Coursera)– This is another best course available online. This course not only teaches you R programming but also teaches you data science tools and techniques, including getting, cleaning, and exploring data. You can check the course details here.
Now, let’s move to the next skill required for Data Analyst-
2. Statistics-
In order to become a successful data analyst, you should have a knowledge of Statistics. Statistics knowledge will give you a ability to decide which algorithm is good for a certain problem.
Statistics knowledge includes statistical tests, distributions, and maximum likelihood estimators. All are essential in data analysis.
As a Data Analyst you have to find useful insights from the data, so, that’s why statistics knowledge is crucial for you. Now, you may be thinking, Ok fine! Statistics knowledge is required, but from where to learn?
So, if you are thinking the same, then don’t worry. I have chosen some specific courses for Statistics. These courses will give you in-depth knowledge of statistics.
Separate Statistics Course-
- Statistical Inference (Coursera)– If you are thinking to gain statistics knowledge, then this course is best for you. After completing this course, you will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data. You can check the course details here.
- Basic Statistics (Coursera)– This is another course specially dedicated to Statistics. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. You can check the details of this course here.
Now, let’s move to the next skill required for Data Analyst-
3. Mathematics–
As a data analyst, you have to deal with numbers. That’s why strong knowledge of Math is required. You should be familiar with multivariate calculus and linear algebra. Along with that, you should have an understanding of matrix manipulations, dot product, eigenvalues and eigenvectors, and multivariable derivatives.
You can gain Mathematics skills from these courses-
- Data Science Math Skills (Coursera)– This course is specially dedicated to those who want to learn Math for the Data Science field. In this course, you will learn all the math required for Data Science. You can check all the course details here.
- Mathematics for Machine Learning Specialization (Coursera)– This is a Specialization Program dedicated to Data Science Math. In this program, you will learn Discrete Mathematics relevant to Data Analysis, Calculus, a linear algebra that is used in data analysis, and probability theory and statistics. You can check the course details here Mathematics for Machine Learning Specialization.
Now, let’s move to the next skill required for Data Analyst-
4. Data Wrangling-
Data wrangling is all about data collection and data cleaning. So, for that, you should have knowledge of database systems- both SQL-based and NoSQL-based. You should also be familiar with relational databases such as PostgreSQL, MySQL, Netezza, and Oracle, as well as Hadoop, Spark, and MongoDB.
I have selected some separate courses for Data Wrangling-
- Databases and SQL for Data Science– This course is offered by IBM. In this course, you will learn relational database concepts and foundational knowledge of the SQL language. For more details, you can check here.
- Getting and Cleaning Data– This course will teach you how to collect data from the web, from APIs, from databases, and from colleagues in various formats. This course will also cover the basics of data cleaning. For more details, you can check here.
5. Data visualization–
As a Data Analyst, you have to showcase your findings in a visual form, so that stakeholders can understand it properly. This is an important step for a Data Analyst. That’s why the knowledge of Data Visualization is important. And for that, you should be familiar with data visualization tools like ggplot, matplotlib, Seaborn, and D3.js.
You should have knowledge of various Reporting tools like Tableau and power bi. These tools have in-built visualization reporting tools. By drag and drop, you can create a wonderful presentation report.
You can learn Data Visualization from these courses-
- Data Visualization with Python– This course will teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. This course will use several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium. For more details about this course, you can check here.
- Data Visualization with Tableau Specialization– This specialization program is intended for newcomers to data visualization with no prior experience using Tableau. At the end of this program, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. For more details about this program, you can check here.
- Learning Python for Data Analysis and Visualization– This is another course from Udemy, that will teach you about Data Visualization. You can check the details here.
Now, let’s move to the next skill required for Data Analyst-
6. Machine Learning-
After having all previous skills, it’s good to have a basic knowledge of Machine Learning. Not all Data Analyst have Machine Learning knowledge, but if you want to get extra privilege, its better to have Machine Learning skills.
You don’t need to learn theory and implementation details behind all ML algorithms. All you need to know is its pros and cons, as well as when to and when not to apply these algorithms to a dataset. These are some important algorithms of ML, you can learn- principal component analysis, neural networks, support vector machines, decision tree, logistic regression, and k-means clustering.
This single course is enough for you in order to get the basics of Machine Learning-
- Machine Learning (Coursera)– This is no doubt one of the Best Online Courses for Machine Learning. This course is created by Andrew Ng the Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University. For more details about this course, you can check Machine Learning.
So, these are some Technical skills required for Data Analysts. But along with these technical skills you should have some business skills. So, let’s have a look at the business skills required for Data Analyst-
Business Skills
You should have following Business skills in order to become a Data Analyst-
- Communication Skills- Data Analyst should have good communication skills. Why? because after finding valuable information from the data, the data analysts have to present their findings to the stakeholders. So, in order to present and tell the data story, you should have good communication skills.
- Data Analyst should be Creative– Data Analysis requires creative thinking. And this creative thinking depends upon technical skills. If you have a strong statistical knowledge, then you can easily think creatively related to data.
- Story-Telling Skills- As a Data Analyst, you should have story-telling skills. Because you have to tell everything related to data to the stakeholders.
So, as a Fresher, if you have all these skills, then you are ready to get a job as a Data Analyst. I have discussed all the important skills required for Data Analyst along with resources for learning all these skills.
Note- The resources that I shared with you are dedicated to specific skills. But, if you want a complete course or Specialization for Data Analyst, then you can choose any one of these-
- Data Analyst Masters Program– This is the complete Master’s Program for Data Analyst offered by Edureka. This Master’s program will cover all discussed skills. This is a complete program for Data Analyst. After completing this Master’s program, you will get a Data Analyst Certificate from Edureka. For more details regarding this Master’s program, you can check here.
- Become a Data Analyst– This is a NanoDegree program offered by Udacity. This course will cover Statistics, Data Wrangling, Data Visualization with Python. Enroll in this Nanodegree program only if you have Python Knowledge. If you are not familiar with Python, then this is not for you. First, learn Python from the resources that I have shared. You can check more details related to this course here.
- Data Analysis with Python– This course is offered by IBM and available at Coursera. In this course, you will learn Importing Datasets, Cleaning the Data, Data frame manipulation, Summarizing the Data, Building machine learning Regression models, Building data pipelines, etc. For more details, check it out here.
- Data Analysis & Visualization Bootcamp- This course is offered by Udemy. This course will cover the basics of Data Analysis. But if you don’t have basic mathematical and Python knowledge, then this is not for you. For more details regarding this course, check here.
So, these are some dedicated courses and specialization programs available for Data Analyst. I have filtered these courses from hundreds of courses available online. I hope you will find these courses helpful.
For more details regarding Data Analyst Certification Courses, read this article- Data Analyst Online Certification to Become a Successful Data Analyst
So, once you have gathered all these skills, the next step is building a strong Resume. So, in order to know how to make a strong resume, you can skip the next section and directly jump into the “What’s Next Step?” section.
Data Analyst Career Path for Experience
As a experienced mean, I am assuming either you are Software Engineer or you have experience in Mathematics field. First of all, Congratulations! for choosing a correct direction for you career.
So, if you are a Software Engineer, then definitely you are familiar with programming languages. But you don’t have enough mathematical knowledge.
Am I Right?. So, let’s see how you can become a Data Analyst with having a strong Programming Knowledge-
Career Path for Experience in Programming
As you have programming knowledge, that means you have already one major or most required skill for Data Analyst. All you need to do is just learn these following skills, in order to become a Data Analyst-
1. Statistics and Probability-
As a Data Analyst, you have to find useful insights from the data, so, that’s why statistics knowledge is crucial for you. Statistics and Probability knowledge include statistical tests, distributions, and maximum likelihood estimators.
Statistics knowledge will give you an ability to decide which algorithm is good for a certain problem.
The next topic, you need to learn is-
2. Multivariate Calculus and Linear Algebra-
These math skills will give you a ability to understand how machine learning actually works. These math skills will help you to put your next step as a Data Scientist from Data Analyst.
In order to learn all the math required for Data Analyst role, I have chosen the Best Course for you. This course will cover all the math required for performing data science work.
Course for Mathematics-
- Mathematics for Machine Learning Specialization (Coursera)– This is a Specialization Program dedicated to Data Science Math. In this program, you will learn Discrete Mathematics relevant to Data Analysis, Calculus, linear algebra that is used in data analysis, and probability theory and statistics. You can check the course details Mathematics for Machine Learning Specialization.
Along with math knowledge, you should be familiar with Data visualization and Data Wrangling.
For Data Wrangling, you should have knowledge of database systems- both SQL-based and NoSQL-based.
As a Data Analyst, you have to showcase your findings in a visual form, so that stakeholders can understand it properly. That’s why the knowledge of Data Visualization is important. You should have knowledge of various Reporting tools like Tableau and power bi.
If you are familiar with Data Wrangling and Data Visualization, then it’s good. But if you don’t have any knowledge, then you can refer these courses-
Courses for Data Wrangling and Data Visualization-
- Getting and Cleaning Data– This course will teach you how to collect data from the web, from APIs, from databases, and from colleagues in various formats. This course will also cover the basics of data cleaning. For more details, you can check Getting and Cleaning Data.
- Data Visualization with Tableau Specialization– This specialization program is intended for newcomers to data visualization with no prior experience using Tableau. At the end of this program, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. For more details about this program, you can check Data Visualization with Tableau Specialization.
So, that’s all you need to learn in order to become a Data Analyst as a Strong knowledge of Programming. After having all these skills, the next step is building a strong resume. You can skip to the next section – “What’s the Next Step?”
Career Path for Experience in Mathematics
So, you have strong Mathematics knowledge. That’s good. Because in Data Analysis knowledge of Statistics and Maths is compulsory. But the Data Analyst job requires much more. So, let’s see what you need to learn-
Programming Knowledge-
You need to have knowledge of basic building blocks of programming and that is- Variables, control flow, loops, functions.
You should also have an idea of Debugging. Debugging means finding error in your code. That is important to know.
Along with that, you should be familiar with Object-oriented programming. Some more advanced topics include Data Structure, Algorithms, and Software design pattern.
The mostly used programming languages for Data Analyst are Python and R. So, You can choose between Python and R.
Now, you may be thinking, “Ok I got the topics, but from where I can learn?”. So, if you are thinking the same, then don’t worry. I have chosen some Best Online courses available for Programming.
For Python
- Python for Everybody (Coursera)– This is one of the Best Online Courses available for Python Beginners. Approximately 1.6M students have been enrolled in this course. You can check out this course here-Python for Everybody .
- The Python Bible™ | Everything You Need to Program in Python (Udemy)– This is another best course available for Python Beginners. You can check the course details here.
For R
- R Programming A-Z™: R For Data Science With Real Exercises! (Udemy)– This course is for complete Beginners in R. After completing this course, you will have complete knowledge of R Programming. You can check the course details here.
- Data Science: Foundations using R Specialization (Coursera)– This is another best course available online. This course not only teaches you R programming but also teaches you data science tools and techniques, including getting, cleaning, and exploring data. You can check the course details here.
So, that’s all you need to learn to become a Data Analyst. After having all required skills, now, let’s see the next step-
What’s the Next Step?
Once you gathered all required skills, its time to showcase your skills. You can showcase your skills via Resume. Resume is the first things, that Recruiters will see. That’s why your Resume should be strong and make yourself apart from others.
So, let’s see how to build a strong resume whether you are Fresher or Experienced-
Build a Strong Resume
Let’s see a step by step guide to build a strong resume-
Step 1- Template Selection
Before writing a resume, you need to find out a template for a resume. For data science or machine learning resume, choose a very clean and simple template.
Things you need to take in mind while choosing a template-
- The template should be classic.
- Avoid templates with so many graphics. It gives a bad impression to the recruiter.
- Don’t hesitate about white spaces. That means don’t try to fill the full page with text. Leave some white space that looks clean.
- Don’t write a long text like a story. It should be precise and simple.
- If you are an experienced guy having experience in different companies and found tough to put all details on one page. Then don’t need to write all the experience details which are not relevant to the Data Analyst field. Only list relevant experience in the resume.
NOTE- Most of the companies are using ATS( Applicant Tracking System). This is an AI-based system which screens lots of resume in less time. So for ATS, a single column resume is the best bet because it is easy to understand.
Step 2- Write Header
In the Header Section of your resume, you need to write your name and contact information. This should be at the top of the page.
you need to take the following things in your mind-
- Write your name in place of the “Resume” title.
- Don’t write full physical address, just write City and State.
- Always make sure, what phone number you are writing is on working conditions. So that recruiters can easily contact you.
- Give your Linkedin profile link and Github link. So that recruiter can have a look at your projects whatever you have done.
Step 3- Career Objective.
A career objective defines your motivation. It should be simple and cut to cut. If you are fresher, then you should definitely add a career objective in order to show your passion for the field.
Step 4- Projects or Publications
In that section, you need to write what you have done previously on Data Science Field. Whatever projects you have done like data analysis projects or machine learning projects, you need to write in that section. You can also mention your published papers in the data science field.
Don’t add very simple projects just like hello words or kiddish projects. Only add those projects which will give a good impact on the recruiter.
Step 5-Experience
If you are an experienced guy, then you need to write the experience details in that section. You should write the most recent experience first. If you have more than a five-year experience, then no need to list all the details. Just write the relevant experience which suits the job profile.
One more important thing, if you have more than a six-month gap in your career, then you need to mention the reason.
BUT,
If you are fresher, then you are thinking what should I write in that section? well… no worries. You can also write the following things in the Experience Section.
- You can mention any internships, which you have done in Data Analyst field. No matter, you have done from any reputed company or from a small place. You can mention along with the internship period plus what you have done.
- You can also mention your college projects that include data analysis work. When you were learning data analytics you have done some practical exercise, you can also mention them.
- Mention your volunteer work related to data analytics.
Step 6- Education
The next section is education. You can showcase this section first, but if you have done various projects and you have experience in data analytics then put them first. But if you are fresher, then you can put the education section first then projects.
In that section, you can also mention the key courses which suit the job profile. And Don’t afraid to write a long education section, because it gives a good impact.
Step 7- Skills and Certificates
In that section, you need to mention whatever skills you have, suitable for Data Analyst. The skill section is mandatory for technical jobs. So you can’t avoid this section. Write your strongest skills first, so that recruiter will focus on that part.
Some important points to consider while writing this section-
- Write only those skills which you have. I have seen many people writing skills which they don’t have. Just for showcasing. But this will harm you in the interview process. This will make a bad impression when interviewer ask you some question on that skill listed but you can’t answer. So make sure, write only those skills, which you know very well. This is very important.
- Read the job profile and what skills they require, then see how many skills you have. Suppose in the job description they mentioned Good Knowledge of Python, and you have good knowledge in Python, then definitely write “Good Python Knowledge” as the first skill. You can repeat the same for other skills too, just compare your skills and the skills written in Job Description.
- If you have done any certification courses on Data Analytics or in Machine Learning then also mention in your resume.
Step 8- Final Touch
After finalizing your resume, you need to check for grammar and spelling mistakes. You can give your resume to your trusted friend. They can check for grammar mistakes.
But if you don’t wanna give it to your friends then you can check it on Grammarly. Because of any grammar or spelling mistakes, your full work will be wasted. So thoroughly check for grammar and spelling before sending it to the company.
So, that’s all about Resume building for Data Analyst Job. I hope now you have a clear road map for Data Analyst Job. Now, it’s time to wrap up.
Conclusion
In this article “How to get a data analyst job?”, I tried to give you a complete road map for Data Analyst Job. In this article, you have learned the following-
- What is a Data Analyst?, Roles and Responsibilities of Data Analyst, Is Data Analyst a Good Career? and How much Data Analyst Earn?
- Data Analyst Career Path with no experience and with experience.
- How to build a strong Resume for Data Analyst post?
I hope now you are ready to become a Data Analyst and no one can beat you to become a Data Analyst. Now you got a clear answer to your question, “How to get a data analyst job?“. If you have any doubts or queries feel free to ask me in the comment section. I am here to help you.
All the Best for your Career!
Happy Learning!
If you are looking for Data Scientist Online Courses, You can check this article- Best Online Courses for Data Science to become A Skilled Data Scientist
If you are looking for Certification Course for Business Analyst, you can check this article-Certification Course for Business Analyst You Should Know
FAQ
A Bachelor’s Degree is required for most of the entry-level data analyst jobs. And Master’s degree is needed for upper-level data analyst job.
You should be a story teller person, a commercially intelligent, a creative thinker with respect to data. Along with that you should have good communication skills.
Data Analyst analyze the data. As a Data Analyst, you should be familiar with programming languages, that’s why you can say that Data Analyst is and IT job.
Its not hard to get an entry-level data analyst job. You just need to have skills that I mentioned earlier. But to succeed as a Data Analyst is hard. That mean how you grow as a Data Analyst after getting a job depends upon how much in-depth knowledge you have.
It depends upon the job requirement and the company you are working. But as a Data Analyst you don’t need to write a heavier code.
In short, yes. Python is a good choice to perform data analysis tasks.
Definitely Yes. Due to the high rise in data, data analyst are high in demand. That’s why companies are offering a High salary.
Yes. As a data analyst, you should have a good grasp of mathematics.
Thank YOU!
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Though of the Day…
‘ It’s what you learn after you know it all that counts.’
– John Wooden
Written By Aqsa Zafar
Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.
Thank you for sharing knowledge.
I love to study in data science field because I am a statistician and also I had got master degree in computer.
I would like to learn in data science; big data and machine learning.
Thank you so much.
Thank You!
Thank you for sharing the useful information about Data Analyst.
I love to study in data science because my field is Computer science with programming language
And I working with data, my favorite field.
I would like to learn in Data science.
Thank you very much for sharing the best and useful information.
Faridullah Ahmadi
I am glad that you liked my article.
Very vast information 😲😱 It’s scary but indeed very informative. Thank you for your efforts in creating such a crystal clear data.
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