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title: 'A guide to becoming a data analyst: roles and responsibilities, skills required'

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<h1>A guide to becoming a data analyst: roles and responsibilities, skills required</h1>

![](https://i.imgur.com/q5kp4ry.png)


Data analytics is a powerful weapon for organizations, helping them shape business decisions and increase their effectiveness. 

If you are fond of playing with data, spotting patterns, and extracting valuable insights, you might consider becoming a data analyst.  Increased data generation and awareness have prompted many to think and plan further. But to become one, you need to understand the roles, responsibilities, and [essential skills required for a data analyst](https://codebasics.io/blog/learn-top-data-analyst-skills-in-just-3-months).  

Are you worried because you don’t have answers to these questions? You need not. With this blog, you will find answers.  We will start by discussing the roles and responsibilities of data analysts. 

<h2>What do data analysts do?</h2> 

Data analysts are specialists responsible for collecting, mining, analyzing, and interpreting data to find solutions to business problems. 

This makes you think that data analysts are those geeks with high-end gadgets involved in number crunching all the time, right? It isn’t true. There’s more to their work. Their work can be divided into the following steps: 

<li>They extract data from various sources using SQL, Python, etc</li>
<li>Clean it to erase all the outliers and inaccuracies</li>
<li>Use analytical thinking to find insights into the data</li>
<li>Visualize the results to stakeholders and leadership and Contribute to the decision-making process</li>

It’s viable to say they transform the way businesses use data and guide their decision-making. 

Now that you have a clear idea of what data analysts do, we can look at the essential skills required for data analytics. 


<h2>Requisite skills to become a data analyst.</h2>

You need to acquire hard skills and soft skills to become a skilled data analyst. Below, we have briefly discussed some that can help you in your journey. 

<h3>1. SQL for interacting with databases.</h3> 

You will draw insights only when you have data. Large chunks of data are stored in relational databases. Retrieving it for analysis becomes possible with domain-specific programming languages like Structured Query Language (SQL). 

Data analysts must be proficient with SQL, as it helps them talk to data, comprehend what it is saying and pass on the message to other stakeholders. Knowledge of SQL allows you to understand data better, experiment with it, and carry out data analytics processes conveniently. It is one of the hottest skills to acquire in the 21st century if you wish to work intelligently and effectively with data. 

You can be new to the journey and worry about how you can learn SQL. But you need not, as today there are plenty of premium-quality online SQL courses available on the internet that make learning user-friendly and effective. These interactive online courses allow you to factor learning into your busy schedule, as you aren’t bound to a physical campus. Therefore, you can learn without disturbing other commitments. 

What’s better than learning one of the most in-demand data analyst skills from the comfort of your home, and that too at your own pace? 

<h3>2. Python Programming</h3>

Data analysts do not require exceptional [Python programming](https://codebasics.io/courses/python-for-beginner-and-intermediate-learners) skills like software developers or programmers. But learning the language can be beneficial for you to clean, explore, model, and visualize all the information accurately. 

One of the main reasons why data analysts use Python programming for data analytics is the presence of a wide range of libraries that make operations simple and easy. Below, we have listed some Python libraries and their use cases in real life: 

**NumPy:** NumPy provides n-dimensional arrays and supports computing tools essential for data analysis. 
**Pandas:** Pandas library is useful for handling inaccurate datasets, performing mathematical operations, and manipulating datasets. 
**SciPy:** For scientific computation, the SciPy library proves to be effective. It consists of modules for linear algebra, interpolation, etc.
**Matplotlib:** For effective data visualization, Matplotlib comes in handy. 

Proficiency with these libraries will help you gain an edge in data analysis, analyze it better and present effective results to the stakeholders.

<h3>3. Statistics</h3> 

Statistical knowledge helps you organize data, spot patterns, and make visualization easier. 
 
Data analysis becomes a shade better with the knowledge of basic statistical concepts like significance, response variables, etc. These statistical concepts help you with the mathematical analysis of data and infer the larger picture. Moreover, they help you remove unwanted information and catalog useful information in an orderly manner. 

Sound statistical knowledge becomes essential to make data interpretable and usable for further use. Therefore, be great friends with statistics while learning data analyst skills!

<h3>Presentation skills</h3> 

Great research and analysis will help you understand the picture. But great presentation skills will help everyone understand the picture. 

Remember, finding all the sophisticated insights from the data isn’t your only responsibility. Presenting those insights engagingly so that it resonates with the audience is equally essential.

An engaging presentation will help you bring all the stakeholders on the same page and understand your perspective. This way, you will add value to the decision-making process and help the organization move in the right direction. 


<h4>Conclusion:</h4> 

These are some requisite data analyst skills you can learn to build a strong foundation of data analytics. You can learn from online resources if you feel that you aren’t good with these skills. When starting your learning journey it is advised you start your learning journey by learning SQL basics. You can do so with the help of [online SQL courses](https://codebasics.io/courses/sql-beginner-to-advanced-for-data-professionals). But why SQL basics? As we discussed, SQL helps you communicate with relational database systems and extract relevant data. Without that, you can’t move ahead in the data analysis process. 

When it comes to learning, online courses can help you understand how SQL works, its features, and the different commands used for data extraction and analysis. Moreover, they will also help you gain domain experience by providing you with exposure to real-world job assignments. They will help you challenge your analytical thinking and find solutions in a business environment.  It can be a complete package for all your learning requirements and help you to become a data analyst. 

Remember, there’s a lot of demand for data analysts in the industry. And it is critical to stay ahead of the curve, stay relevant, and keep learning.

You can start now, as now is always better than never. 
