What is Exploratory Data Analysis

Now that you have a huge amount of data, you need to analyze it to find anything of meaning or else you might get lost in the sheer volume of it. You have to explore the data with the aim of extracting useful and actionable information from it.

In the following video, Ujjyaini will introduce you to the concept of Exploratory Data Analysis, which as the name suggests, refers to exploring the data for any useful inferences.

Exploratory data analysis (EDA) is one of the most important steps in any kind of data analysis. Say for a salesman, the conversion ratio is very poor. He looks at the data so as to identify the reasons for the poor conversion rate.

Once you have explored the data and have some findings, it is imperative to be able to present it in a format that can be understood by the senior management. This is where reporting comes into the picture.

Before performing further analysis, you clean the data. One faulty reading can spoil the whole analysis. Post cleaning, you perform a deeper analysis to extract patterns from the data to make decisions.

Imagine if Vikas, who normally shops for shoes and phone cases for his Motorola G3, accidentally clicked a link to add a couple of iPhone X to the cart. And Flipkart forms a model of him on the basis of this data. Will this model ever be able to come up with any useful recommendations for him. Seems unlikely, right. That is why data cleaning is imperative to draw any worthy insights from the data.

Additional Resources

You can read more about the above terms at the link provided below.

Exploratory data analysis - EDA

The importance of dashboards - Dashboards

Descriptive analytics - Descriptive Analytics

Why is the cleaning of data important - Data Cleaning