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Finding the Trailhead to your Data Analyst Journey

If you were to ask me as a kid what I wanted to do when I was older, I can promise anything with the word “data” in it, would not have come out of my mouth. I guess that is to say, things have a way of taking unexpected turns, including our interest.

My fascination with data started a few years ago when I got a job as a online reputation manager charged with the task of increasing the volume of my company’s positive online reviews. I wasn’t given any guidance and was told the reason they were hiring was that they had no idea what to do or where to start, and my job was to figure that out.

I sat down at my computer trying to figure out just where to begin. I didn’t have many tools but I realize I did have some access to metrics about our online reviews. As I dove into these metrics I started to uncover layers of data that provided me more insight to get closer to the solution. I could learn where they came from regionally, the volume of reviews in each star category, the common most words in our negative reviews and positive reviews which could help me identify our company’s strength and weaknesses from the customers point of view. I was outstanding by how much this information was helping me to form an actual applicable strategy to improving our online reviews. I wanted to learn more.

The story goes on, but that’s for another day. In short, this data help me form a strategy that within six months of execution had increased the volume of our positive online reviews by 67 percent. I was hooked.

Since then I steered my marketing career towards one of data analysis, data visualization, and data science. Much like my experience with trying to figure out where to start in my new job I mentioned before, the hardest part of beginning a career in data science has been figuring out just where to start. Being new in the field it is a struggle to be able to identify what content is appropriate to help you begin. Should I use a code learning site like or Should I read articles? Which youtube videos should I watch? What coding language should I focus on? Once I decide, where and how do I start learning? I can confidently say that this part, thus far, that last question has been the most discouraging to me. Once I finally found the trailhead to begin my journey, while the trail can be a little rocky and difficult sometimes, I can at least see the next steps I have to take.

So here are my recommendations for best places to start your data analyst journey:

  • — Join the Kaggle community. Not only is it a great place to learn how to use python for data science and practice on datasets, its also a great community to connect and discuss common concerns with other people who share your interest. My recommendation: sign up and immediately take the free course Intro to Programming, from there take the Python course. This is the best possible start to your journey, in my opinion.

  • Download the audiobook “Build a Career in Data Science” — I listened to this book while on a roadtrip and it really helped outline for me the process and landscape of a career in data science. It helped remove a lot of the mystery for me, and gave me confidence to pave my own path.

  • Join these helpful resources to explore daily articles to read:,,

I truly believe that this is the best free to low cost trailhead to begin your data science journey. It took me months of sorting through a jungle of resources until I finally found these simple things to really get me start. I hope this can at least help you save time and get the quick kickstart you need to explore this fascinating field.

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