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.
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.
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.
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.
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.
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.
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.