Analytics

Data Analyst – Roadmap In 2022

Leo Arruda's avatarPosted by

The first question to our mind is, who is a data analyst? What do they do?
Simply put, a data analyst is responsible for collecting, processing, and analyzing data to find sensible insights for decision-making.
In most cases, an analyst will work on the raw data and grind it to produce action-oriented insights. Most analysts won’t work on core machine learning or deep learning models.
A data analyst will use multiple tools to process the data and work with it. Having experience in working with different tools and statistics is vital for them.
We will also discuss each skill and related certifications in the following blocks.
In this article, you’ll find the following sections:

1. Statistics

For every data professional, stats and math are the must-haves. Because without the knowledge of stats and probability, one cannot interpret the data effectively.
Some of the major topics include descriptive and inferential statistics. If you are a beginner, you can spend 2-3 weeks dominating these topics and working on some problems for the hands-on experience. Trust me, the time you put into 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 Excel has its importance to date.
It provides many functionalities such as charts, analysis, VBA, Macros, Filters, and Formulas. The Pivot table, VLOOKUP, and the new XLOOKUP functions are analysts’ most commonly used functions in excel.
So knowing 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 possible to master these skills.

Top Certifications –

  • 365 Data science – Introduction To excel. This is one of the underrated courses, 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 the 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. You should also be familiar with databases and their management as an analyst. You have to perform the CRUD operations on the company’s database. For this purpose, no other tool is as flexible and scalable as SQL.
It would be best if you mastered 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 also work on them using Python, R, and SQL.
The BI is mostly used for dashboarding, report-making, and data visualization. Some of the top BI tools for you in 2022 are Tableau, PowerBI, and Looker.


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

PowerBI Dashboard

Top Certifications –

5. Programming Language

Yes, having a good hold on one or more programming languages will be very helpful for you. Though some 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 Matplot lib in Python and dplyr, ggplot in R.
Strong knowledge of these libraries can help your analysis be effective and to the point.

Top Certifications –

6. Business Acumen

Business acumen plays an essential role in structuring business data analytics. After all, data does not exist in a vacuum, and the context your business provides clarifies and puts your analyses into perspective. In determining the question, you know what is best for your business and will choose which issue you find the most important to resolve.
Business acumen will govern the data process and help you make decisions. It is an underlying theme in each process step, from asking the right question, choosing the correct data, and explaining the analysis to its end consumer.
Good data analysis and business acumen are complements, not substitutes.
Pick up the domain knowledge of the industry you would like to specialize. i.e. Finance, Healthcare, Sports, etc.

7. Portfolio & Resume

The final shot should be on your portfolio and resume upon learning all the skills. One should always work on some real-world projects which require all your acquired skills to play.
Also, you must spend some time on your resume highlighting your skills, projects, and experience. All your handwork can only be presented as a resume and your rich and diverse portfolio.
One last but most important skill is data storytelling. You can be powerful 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 crucial in building your career in the data domain, particularly analytics.

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