How to prepare for a career in data analytics

There are scores of different tools and technologies that analysts are usinog on a daily basis to get the most out of the data at hand. If you set your mind to it you can learn and master as many of these tools as you wish. Guiding you through those tools and technologies is not the purpose of this post. We will talk about the one thing that is common to every analytics project: Identifying problems and trying to solve those using data.

Rudiments of analytics

The journey of any analytical query starts with a few simple questions. In the case of an online business there are questions like how often does a person A visit your website? How did A know about your website? Are there others like A who are looking for the same thing? What are they searching for? How old are they? Where do they come from? What will they look for in the next quarter. If we look at these questions, we will see that we are just trying to peep into what has happened and trying to assume what might happen, at a larger scale. These answers are easier to find if compared to questions like what should our strategy be if we want to convert A into a loyal customer? These questions are the bed rocks of data analytics. Your preparation starts with understanding the significance of these.

Business acumen

You need to develop an acute understanding of the factors that work like the wheels under the business you are serving. For instance, if you are working for an e-commerce company your business thrives on the understanding of consumer behaviour at different places and times. Your analytics efforts should comply with these. The tools are not the hero. You are. If you know your business from insight out, it will help you decide on which data scource to focus on and which one to keep on a low priority.

Habit of working with machines

Process automation has become a huge part of business process management. Under the current circumstances your success and sustenance as a data analytics professional depends on your ability to work in tandem with automation programmes and to monitor and control the same. Choose your big data courses according to these plans and make sure you do not fall behind. The machines will not take your job but someone with a better understanding of process automation might.