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In this article, you will get to know all the aspects and a clear roadmap for becoming a Data Analyst. After reading this article you can kickstart your career to become a Data Analyst without wondering what a Data Analyst job is really about.

So let’s get started:

Academic Background

The first step is to choose a degree. In the IT sector, you have multiple options to choose your desired degree.

Such as Bachelor's Degree in Data Science, Computer Science, Software Engineering, Statistics, Mathematics and Analytics.

Having a degree is a plus point for you but even if you don’t have one you can still become a Data Analyst with the required skillset.

Skills

So to become a Data Analyst you need to have certain skills that will help you pursue your career as a Data Analyst.

Based on the role of the data analyst, skills can be divided into three categories:

• Technical Skills
• Analytical Skills
• Soft Skills.

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Technical Skill

Technical skills include Excel, Databases, Coding, Data Visualization, Mathematics and Statistics.

Let’s explain one by one:

Excel

The first one is Excel. Knowing how excel works is an essential part of the data analyst role. In school and college, students learn the basics of excel.

But to become a data analyst it would necessary to master Excel before you start coding related work.

You should know at least important features such as data filtering, functions and formulas etc. Charts Pivot tables and macros. These sorts of skills will help you to pass the data analyst's interviews.

Databases

As a Data Analyst, you have to store data somewhere. For this, you should have knowledge of Relational Database Management Systems.

SQL knowledge is required for this purpose so that you can retrieve that data.

Programming knowledge

Python, R and Saas are important programming languages to become a data analyst.

Python is the most important.

Some major Python libraries include NumPy, Panda, PyTorch and TensorFlow. These python libraries will be helpful while cleaning and storing the data.

R comes on the second number but it also depends on the requirement of the company whether they prefer R or Saas for their work.

Data Visualization Tools

One of the data visualization tools is Excel. However, when you have a huge amount of data you will need advanced data visualization tools so that you can manage your data more effectively.

Some important tools include Tableau and Power BI.

Mathematics and Statistics

To master these sorts of skills bachelor's degree in related fields will be helpful but even if you don’t have such a degree you can learn from plenty of free internet resources and find your way to becoming a Data Analyst.

Basic maths and analytics knowledge will help you to analyze data in a better way.

Analytical Skills

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After you have learned some technical skills. It’s a time to focus on analytical skills.

The skill of analyzing, investigating, researching, and providing solutions based on your understanding.

• Critical Thinking
• Research Analysis
• Data Analysis

Critical Thinking:

This means how well you are able to understand the problem.

How well you are able to connect the dots between ideas that you have and the data that you are provided with.

No matter how difficult the problem may be but your main task is to critically think about the solution. So that you are able to help the clients to make better decisions.

Research Analysis:

You identify what your problems are and based on these problems you need to identify from which credible sources you gonna extract the data.

The more well researched your data is the more accurate your results will be. Brainstorming different ideas and the basis on which you find your solution which is based on your research analysis.

Data Analysis:

It is obvious that as a Data Analyst your main task is to analyze the data. As your data is in large amounts so you have to draw insights.

Not only this but you need to interpret the data according to your requirements and draw better insights so that you can help decision-makers to make better decisions.

Soft Skills

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You need to be an excellent communicator.

If you learn the mastery of becoming a Data Analyst and learn all those advanced technical skills but are unable to explain your results and findings to your team and clients then your work is useless.

Your final task is to explain your data in the form of a story so that your team will be able to understand what your data is all about.

Mainly three kinds of communication you need to learn:

• Verbal
• Written
• Visual

Verbal

Verbal means explaining while speaking with colleagues and clients like in meetings and phone calls.

Written

Written includes writing your documents and reports. This will help others to understand your findings and you can update your documents anytime in the future.

Visual

Visual means if you ask to explain your thoughts to a large audience or in a large meeting room and you feel hesitant then this job role is not for you.

As a data analyst, you need to share your works and thoughts with so many people. Fortunately, you can learn all those skills and improve over time.

Some insights to becoming a Data Analyst.

• While making a resume it will be helpful to add your soft skills and analytics skills along with your technical skill.

• If you don’t add your soft skills and other creative skills like leadership ability, critical thinking and teamwork then your CV or resume might be filtered out in the first stage.

• Another thing is doing online courses and certificates which make your profile attractive to the interviewer.

• Join LinkedIn Groups and other online useful resources so that you will get to know the latest trends and what other people are working on in the field of Data Analysis.

• You can also share your own projects with other people of similar interests.

• Some other senior job roles like Data Science and Data Engineering also have some common skillsets required. So after you have enough experience in Data Analysis you can switch your field to more Data related work.

• Look for the new job roles and job descriptions via LinkedIn and other similar resources so that you are well aware of what sort of skillset companies demand that may not be included in this article.