// Tutorial //

Data Analyst Learning Roadmap For Aspirants In 2022

Published on August 3, 2022
Default avatar
By Prajwal CN
Developer and author at DigitalOcean.
Data Analyst Learning Roadmap For Aspirants In 2022

While we believe that this content benefits our community, we have not yet thoroughly reviewed it. If you have any suggestions for improvements, please let us know by clicking the “report an issue“ button at the bottom of the tutorial.

Want to become a Data Analyst? Big data is set to have a market of $300 Billion in 2022 globally. Data-related roles such as data analyst, data scientist, data engineer, data architect are booming and IT companies are in a huddle to hire such people who are having skills for these roles.

One of the major attractions in these roles will be the salary component and the growth. Having tons of data is being collected every second, the data professionals are the need of the hour.

In this article, we will be talking about one of the fascinating careers in the data domain i.e**. Data Analyst**. We will be talking about the Data analyst roadmap for the aspirants in 2022.

In this article, we will be talking about different skills needed to be excelled to become a data analyst. I will be discussing the tools, skills, and the best certifications to show your excellence on these. Let’s roll!


Learning Roadmap for a Data Analyst

data analyst roadmap

The very first question to hit our mind is who is a data analyst? What do they do?.

In simple words, a data analyst is responsible for collecting data, processing it, and analyzing it to find sensible insights for decision making.

In most cases, an analyst will work on the raw data, grind it to produce action-oriented insights. Most of the analysts won’t work on the core machine learning or the deep learning models.

A data analyst will make use of multiple tools to process the data and work with it. Having experience in working with different tools and statistics is most important for them.

In the next blocks, we will be discussing each skill and related certifications as well.


1. Statistics

For every data professional, stats and math are the must-haves. Because, without the knowledge of stats and probability, one cannot able to interpret the data effectively.

Some of the major topics include descriptive and inferential stats. If you are a pure beginner, you can spend 2-3 weeks mastering these topics and work on some problems for the hands-on experience. Trust me, the time you’re putting on these is worth a million.

Top Certifications -


2. Excel

Excel is one of the widely used tools for data processing and analysis by data analysts. We may have many other tools to work with data, but to date, Excel has its importance.

It provides many functionalities such as charts, analysis, VBA, Macros, Filters, and Formulas. The Pivot table and VLOOKUP functions are the most commonly used functions on excel by analysts.

So having knowledge of advanced excel topics will convey a serious message to the employer. Hence, I suggest you pursue some of the best courses and practice as much as you can to master these skills.

Top Certifications -

  • 365 Data science - Introduction To excel. This is one of the underrated course but it offers more than you need to learn about Excel for data analysis.
  • Rice university (Coursera) - Intro To Data Analytics using Excel. This course is a part of Business stats and analysis specialization and teaches you all about excel from basics to advanced level.

3. SQL

No one other than a working data analyst can tell us more about the importance of using SQL in the analysis. As an analyst, you should be also familiar with databases and their management. You have to perform the CRUD operations on the company’s database. For this purpose, there is no other tool as flexible and scalable as SQL.

You have to master some of the topics such as Joins, Table operations, Unions, group by, order by, and more to perform effective analysis.

Top Certifications -


4. Business Intelligence Tools

Business intelligence or BI tools are the most used tools for business analysts and data analysts. You can work on them using Python, R, and SQL as well.

The BI is mostly used for dashboarding, report making, and for data visualization. Some of the top BI tools for you in 2022 are Tableau, PowerBL, and Looker.

You can follow the official documentation, user tutorials on their respective web pages. But if you want to pursue certification in mastering them, then you can follow the below courses.

Top Certifications -


5. Programming Language

Yes, having a good hold on one or more programming languages will be very helpful for you. Though some of the firms don’t care much about a programming language for analyst roles, having good knowledge of them will be handy.

I strongly recommend learning Python and R for the same. Both languages offer robust libraries such as numpy, pandas, and mat plot lib in python and dplyr, ggplot in R.

Having strong knowledge of these libraries can help your analysis to be effective and to the point.

Top Certifications -


6. Portfolio and Resume

Upon learning all the skills, the final shot should be on your portfolio and resume. One should always work on some real-world projects which require all your acquired skills to play.

Also, you have to spend some time on your resume to highlight your skills, projects, and experience as well. Because at the end of the day all your handwork is only can be presented in the form of a resume and your rich and diverse portfolio.

One last but most important skill is data storytelling. You can be very strong at technical skills and tools, but without a good story, all your analysis will be in vain. So, make sure you convey your findings in a proper manner and medium as well.

For Resume -

All these resources and skills covered in this data analyst roadmap are very crucial in building your career in the data domain, particularly analytics.


Data Analyst Roadmap - The End

The data analyst roadmap proposed here covers almost all the on-demand industry skills and is based on the interviews of many working data professionals. I know that you are eager to step into the world of analytics. So, these skills are Gold for you. Spend some time, understand things, practice them, solve some problems, work on real-world projects and you will be ready to be called a Data analyst.

That’s all for now. Happy Learning!!!

More read: Who is a Data Analyst?

If you’ve enjoyed this tutorial and our broader community, consider checking out our DigitalOcean products which can also help you achieve your development goals.

Learn more here


About the authors
Default avatar
Developer and author at DigitalOcean.

Still looking for an answer?

Was this helpful?