Analyst in Action

Let's consider a scenario where you get the unstructured data and you need to derive the insights using it. This sounds so baffling to me and considering it for data-driven decision-making is one of the mistakes. This scenario can be intervened by a basic step i.e. data cleaning. As the name suggests it is the prior step you need to take before deriving insights and creating visualizations out of it.  In other words, it is a prerequisite for data visualization. In my novice experience, I have handled data that arrived from a variety of sources also entered manually which can escalate the chances of getting duplicate values and wrong values which is needed to be removed before taking it further. All these steps may include eliminating some values or replacing some data so that the data is befitted for further visualization. In today's blog, I will take into account 6 basic steps which prove out to be useful for me in every data cleaning step. All these steps are quite extensivel