Exploratory Data Analysis (EDA) is an approach that is often used to analyze a certain dataset by visually present it. EDA is often used before doing model development for machine learning. Since the dataset can have up to thousands of rows and several different columns, it can be quite overwhelming and unclear for the stakeholder to see the dataset. Not to mention, it will be very time consuming and eventually, the stakeholder will get bored by looking at the thousands of rows of data. Thus, visualization can act as a perfect aid to help the stakeholder to analyze the data easily and efficiently.
By using this approach, we can display the dataset in a better and nicer way. We can also summarize the whole dataset into something that will be easier to analyze and choose only required and critical information.
There are several ways or software that we can actually use to do Exploratory Data Analysis (EDA). For instance, we can use Power BI in which we will be using for this project, Python, Tableu, Chartio and other software.
I will explain further regarding our EDA (dashboard) on the next page!