This is my maiden post so before I get into things I thought I should introduce the reason for this blog. Essentially, I’m looking to drive my career towards Data Analysis (or some associated field), but I don’t currently work at Data Analysis (DA). In my current role a kind of analysis of data does get performed, but it’s not DA as it’s understood when companies are looking for Data Analysts. So I wanted to come up with a platform to demonstrate my passion for and knowledge of DA.
An obvious solution is to develop some sort of portfolio of work that I can point to as evidence that I at least have some chops. Credit where it’s due, I was inspired by a friend who began a blog on the subject he was passionate about in order to have something to point to during interview situations, among other reasons. Thanks to Maciej of osintme.com. And so the idea for this blog was birthed.
At this stage the plan is to attack DA topics and when I come across topics that I can turn into a blog post that’s what I’ll do. It will mainly be instructional and as a refresher for me to go back to when necessary. At least in the initial stages while I get up to speed.
It is a relatively natural follow on from DA to also have an interest in Machine Learning (ML), and I do have such an interest. Once I got up to speed on DA I was going to push into ML eventually.
I was also pushing myself to get up to speed on cloud technologies and I chose the route of Amazon Web Service (AWS) due to their size and scale. Also in their favour are the certifications available for the use of AWS services.
This blog was on my todo list as a task to begin in August. I explained my interests in ML and AWS because I came across a very compelling course on Udacity which could lead to a Machine Learning nanodegree scholarship called the AWS Machine Learning Scholarship Program. More information at the program website. Naturally enough, I had to sign up, it’s just too perfect a combination of my interests not to sign up!
So why did I move up my blog timeline? Let me explain.
My plan was to complete the Intro course that leads to the Scholarship. But in just a few lessons I was hit with a problem that I didn’t know how to solve. I’m fairly sure that at some point in my life I was capable of solving it, but it’s been a long time since then. The problem was a relatively simple problem, or at least it should be for a Data Analyst. It was simply to find the probability of a certain result in a distribution.
This is one of the most basic functions of DA. So if I want to move that way, I better (re)learn how to work with distributions. And what a waste it would be to do the learning if I don’t record it somewhere. So the blog is alive!
You are very welcome to be here, stay as long as you like.