How To Break Into Data Analysis

Hello everyone,

My name is Grace, a data enthusiast and this is a thread/article to start you up in data analysis as a complete newbie.

When I started my journey, I went straight into Python without any guidance. This was because the hype was data science, Python. I had heard a number of people mention Python and it sounded like a good place to start. Six (6) months down the line, I was still learning and I was losing interest honestly. I finished my paid course on Udemy and I had to answer the question “What next?” I had been so fixated on finishing the course that I didn’t have an inkling of what the next stage was.

This is not to bore you on my long journey into data analysis but to help any beginner out there who wants to get into data analysis. Here is a compilation of great articles to help you understand what data analysis is all about, free Udacity courses to help you gain momentum in your learning, accounts to follow on Twitter and IG, challenges and hackathons to participate in, and virtual internships to apply all you have learned and boost your confidence.

Let’s get right into it then!

Roadmap to learning data analytics


Data Analysis

First, what is data analysis all about? What skills do you need as a data analyst? What tools would you use?

Skills needed for data analysts


Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. This article further breaks down what data analysis is and the types of the data analysis, Data Analysis: What, How, and Why to Do Data Analysis for Your Organization.


Okay, now you know what data analysis is about to an extent, and you are thinking how to go through the data analysis process. This is time to learn the basics of Python. Python is a popular multi-purpose programming language widely used for its flexibility, as well as its extensive collection of packages, which are valuable for analytics and complex calculations.

How is Python useful for data analysis? Python would help you wrangle, clean, explore and visualize your data using Numpy, Pandas, Matplotlib and so on. This is a free Udacity course on Introduction to Python Programming which is part of the courses for the Data Analyst Nanodegree. Also, you can use this link for the Introduction to Python on W3schools.


Are there better ways to explore and visualize your data, yes! And here comes Tableau. Tableau is a visual analytics platform that makes it easier to create interactive visual analytics in the form of dashboards.

For more information on what Tableau Is and Is Not, check this article by Dan Murray. Also, you can read more on Creating Data Visualizations with Tableau by Jennifer Shalamanov.

How then do I learn Tableau? There is an absolutely free amazing course on Udacity where you can learn, Data Visualization in Tableau. You can also learn how to prepare your data for visualization


At this stage, the word database, database management, must have come up. Or you are wondering, what if I have a table with hundreds of rows and fields but I need only a few? How do I filter and sort what I need? How do I combine similar tables?

It is at the point SQL comes in. Structured Query Language (SQL) is the standard and most widely used programming language for relational databases. It is used to manage and organize data in all sorts of systems in which various data relationships exist.

Udacity also has a free course on SQL for Data Analysis .


One thing that really helped and still helps my learning is communities. A group of people with like interests to interact with, learn from, and share knowledge is really just beautiful.

Here are some amazing communities to join: WeVisualize, DearAnalyst, and DataTech Space.

There is also the Tableau Public community, which is in another league of its own.

Following accounts about data analytics has its own advantages. You get to learn about opportunities and conferences related to data analytics, learn about new tools and basically interact with amazing minds on your tl. For Twitter, I recommend Abby, Zainab, Dzifa, Jessica Uwoghiren, Sarah Bartlett and Sekou Tyler. There are so many other amazing people to follow, and interacting with the people above would help you connect with others.

On Instagram, I follow @datatechspace, @datatechcon and @doingdata.

Projects, Challenges, and Hackathons

Now, you should be pretty confident and be ready to do some projects and get an internship. Great!

Apart from getting data sets from Kaggle to work on, or participating in the hackathons, the MakeOver Mondays data challenges is a good place to get datasets weekly for visualization. The Makeover Mondays challenge would not only help you build data visualization skills but seeing other people’s works is a great way to get inspired with your visualizations. WeVisualize is a great community to share your vizzes for reviews.

The KPMG Data Analytics Virtual internship on Forage (formerly known as InsideSherpa) is a great place to get to understand how data analytics and the analytics department of companies work. Forage gives students the opportunity to learn career skills from Fortune 500 companies through virtual work experience programs.

This was quite lengthy, but I hope the article helps.

Please reach out to me in the comments section for your questions, kindly share this article and don’t forget to clap, comment and follow my accounts.

Follow me on Twitter @gfadeyi and Medium at Grace Ifeoluwa Fadeyi.

Cheers to an amazing learning path.

......becoming the best version of myself

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