Don’t worry, no Python code here (at least in this post). Here I’ll try to straighten out a simple subject – why you need to leverage Python for your daily needs. In case you’re already using it on a regular basis (for some reason I believe you are), please, stay tuned for my blog. I think I have some stuff to publish concerning the subject that may kindle your interest.
Now, let’s get straight to the subject (yes, those three reasons).
ONE – when just collecting data is not enough
But here’s another requirement that is often mentioned in candidate’s specification (this one’s going to be a surprise!) – an ability to expound what really stands behind metrics and figures. And here’s where Python comes into play. With its omni-purpose libraries (like pandas/numpy/seaborn) even a shallow analysis allows you to get precious insights into your data.
Don’t take this one for granted (nullius in verba)! But allow me to demonstrate it to you in my next posts.
TWO – when web analyst becomes data scientist
I personally believe this transformation is inevitable for all who work in this sphere. Being just a web analyst is not enough anymore. Data science (and, of course, machine learning) are at the forefront of data industry. So, if you’re interested in gaining more out of your figures and metrics as a data scientist, consider Python on a first-priority basis (don’t get left behind).
THREE – when dealing with an ETL challenge
Extract data from storage A, transform it, and load to storage B – this is a common task for many web analysts nowadays. I guess the best known example would be loading data to Google Bigquery (or Google Cloud Storage). Certainly, you can always raise to the occasion using any other programming language you feel comfortable with. See, Python is not the only option you have
Start now! There are lots of free multi-language Python courses offered across the web. Don’t be a skinflint. Buy nice or buy twice, remember? Most of coding classes offered by famous platforms (codeacademy, for instance) worth paying money.
As always, I’d be delighted to read your thoughts on the subject in comments below.