So You Want To Do "Data"?

Even stronger than Modi’s wave in 2014 Lok Sabha Elections is the drive of every second-year and third-year in KGP going into the field of data analytics; and, sadly, unlike Modi wave it’s here to stay for many following decades.

Data Analytics as a field has seen nothing less of a bubble than what was seen by the Internet in the era of 2000s when Google, Facebook and, Amazon were blooming. It is a very prospect field in my purview but it is very important to know if it is the field that is made for one or not. I’ve tried to summarise, in this post, a few checks that have helped me see my interest in Data Analytics with a less foggy vision.

The Rainbow [Application]

Seeing into the applicability of knowledge is a great method to gauge interest in a field, in my opinion. One might not find programming exciting but its applications into maths can bring him to programming. Data Analytics can be seen in a similar light; maths and programming might not be your fields of fondness but you might be into drawing conclusions from analysis and reflecting upon them to bring in organizational, structural and behavioral changes.

An article that puts it together in a well structured and summarised manner is 13 Amazing Applications / Uses of Data Science Today: a quick read can give a surface idea about the implementation of data analysis in various fields of customer-centric institutions and others.

The Rain [Coding]

Most of the data analysis requires heavy mathematical skills along with complimentary programming skills; if you like getting your hands dirty in both then DA is THE FIELD for you.

How do I know if I like both, together?

I’ve had the same question and after going through a lot of options, I narrowed down to the resource (given towards the end) which teaches enough Data Analysis and Statistics to make you like it or hate it. The [10-day] course can be taken sitting one hour or so every day [for 10 days] and helps to see if you really want to know more that is there to explore. The best part is that the course is language independent (so is Data Analytics) and you can start with C, C++, Python, R or anything that you already know.

NOTE: It doesn’t make you master in Data Analytics but it gives you enough glimpse to make you aware of what to expect in the field.

The course is Hackerrank’s 10 Days Of Statistics

Data Analytics is definitely one of the most interesting fields to pursue out there and hence, it becomes more crucial to dive into it slowly and step by step. The internet is filled with tutorials that teach Data Analytics, Machine Learning and other buzzing technologies but sometimes it is too late before we realize that it is not the stream we’d like to flow with.

I hope the specified tutorial gives a clearer view of what Data Analytics is and if,

It is what you are meant for