What is data exploration?

Prior to performing deep data analysis, data scientists perform data exploration techniques on large data sets to discover initial patterns, characteristics, and various points of interest.

Data exploration does not aim to uncover every bit of information hidden in the dataset; instead, it is performed to get a broad image of various patterns, trends, and key features.

Data exploration uses a variety of traditional methods and modern automated methods like visualizations and reports.

Data exploration makes the succeeding analysis easier because it provides scientists with a basic foundation that further analysis can be based on; this helps to eliminate irrelevant data paths and points. Sufficient exploration of the data set, along with the usage of adequate visualization tools, can result in useful information pertaining to correlations, patterns, and determining which research paths are worth further analysis.