In The concept of exploring, there are three key elements. First element is the unknown or not familiar aspect, in this case related to information. The second element is the aspect of examining, investigate and uncover what is is unknown and not familiar. Finally, the third element is the tool and technic that can assist in examining and investigating the unmown and not familiar.
The above conceptualization is consistent with Webster Dictionary’s definition of Exploring as “to investigate, study, or analyze : look into… to become familiar with by testing or experimenting” (Source: Exploring Definition & Meaning – Merriam-Webster). In the end, Exploring helps to familiarize the what is contained in the information.
The various elements of data exploration are designed to create a meaningful, understandable, usable mental model. It is also meant to achieve a suitable definition of basic metadata, which includes structure, relationships, and statistics. In layperson’s terms, the ultimate objective of data exploration, and the application of its component parts, is to make once disparate datasets truly usable.
Data exploration isn’t just for finding anomalies, though. Data exploration techniques can be used to identify the structure of a dataset, the relationships between different variables, and the presence of outliers.
