Lier Aing

Self-Paced Learning Data Analytics and Why It’s Not for Everyone

For nearly one year, I try to learn Data Analytics by myself. I use to read books, buy a Udemy course and watch tons of YouTube videos.

Disclaimer: I’m not a Computer Science Graduate, and currently work in HR. So I don’t have a STEM background.

In the early stages of my study, I listen to lots of YouTube and books to grasp what Data Analytics is all about. There are lots of online courses that give free introduction webinars to watch so it’s kind of easy to look for. The introductory part is easy to grasp. I can get the idea that :

  • There are bright prospects in the world of data.
  • Tech companies are looking for data talents, and other companies are catching up. Resulting in high demand for data talents.
  • Data jobs pay well. (I’ll discuss this one in a separate post)
  • Data Analytics/Data Science is based on the intersection of Computer Science(Coding skills, Python, R, SQL), Statistics + Math, and Business.

Here’s the hard part of my self-paced learning. In the early stages of my study, I also did a little research on which skills should I study to be a Data Analyst. On most websites, which explain the learning path to learn Data Science/Analysis, most of them told us to learn the coding part first which is Python and SQL.

On the other side, I also check a couple of Data Analyst job vacancies on Linkedin. And it turns out that Excel and SQL skills are the most essential skills to master.

So I try to learn about SQL and Python by myself and it turns out that:

  • Learning SQL is quite simple. Going through the SQL tutorial seems easier to understand because the language is similar to English.
  • After learning SQL tutorials, I try to analyze Shopee SQL test videos on YouTube. It’s harder than learning the tutorial. Balanced learning of theory and practice is needed for this kind of skill.
  • Learning SQL helps me to learn about tables and data as well. It changes the way I make and use Microsoft Excel. Data validation, primary key, foreign key, and many aspects of excel helps me redefine the way I use excel.
  • Python is hard for someone who has no background in programming like me. I read books about python and even subscribe to an online platform to learn Python. But up until now, I still struggle to understand even Kaggle's basic cases. Need to work harder on this.

So self-paced learning is not an easy thing for me. Even with an internet connection, pc, and tons of resources on the internet. This is not easy, especially for a non-highly discipline person like me.

In the end, I apply to an online course to learn Data Analytics. Though I didn’t succeed in my self-paced learning, I think learning about Data Analytics, or in a broader sense Data helps me a lot in my work and to some extent in my daily life. So it’s not a bad idea to learn Data Analytics.

Update : I’m joining RevoU Data Analytics Course Right now. You can try their free two-week mini course using this link. Click here.

This is the free course

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Mario Olii

Mario Olii

Data Enthusiasts

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