data exploration

This definition is part of our Essential Guide: Guide to telling stories with data: How to share analytics insights
Contributor(s): Ed Burns

Data exploration is the first step in data analysis and typically involves summarizing the main characteristics of a dataset. It is commonly conducted using visual analytics tools, but can also be done in more advanced statistical software, such as R.

Before a formal data analysis can be conducted, the analyst must know how many cases are in the dataset, what variables are included, how many missing observations there are and what general hypotheses the data is likely to support. An initial exploration of the dataset helps answer these questions by familiarizing analysts about the data with which they are working.

Analysts commonly use data visualization software for data exploration because it allows users to quickly and simply view most of the relevant features of their dataset. From this step, users can identify variables that are likely to have interesting observations. By displaying data graphically -- for example, through scatter plots or bar charts -- users can see if two or more variables correlate and determine if they are good candidates for further in-depth analysis.

This was last updated in May 2015

Continue Reading About data exploration



Find more PRO+ content and other member only offers, here.

Join the conversation

1 comment

Send me notifications when other members comment.

By submitting you agree to receive email from TechTarget and its partners. If you reside outside of the United States, you consent to having your personal data transferred to and processed in the United States. Privacy

Please create a username to comment.

Should analysts always start projects with data exploration?


File Extensions and File Formats

Powered by: