Descriptive Analytics
Descriptive analytics is a branch of data analysis that focuses on understanding historical data and providing a summary of past events and patterns. It involves the examination of large datasets to identify trends, patterns, and correlations.
What is Descriptive Analytics?
Descriptive analytics is the branch of data analysis focused on summarizing historical data to describe what has already happened, such as how many candidates applied last quarter or the average time-to-fill by department.
Why does Descriptive Analytics matter?
Descriptive analytics is the foundation every other type of analytics builds on; you need a clear picture of what already happened before you can predict or recommend what to do next.
How does Descriptive Analytics work?
Systems aggregate historical data, like ATS records, into summary reports and dashboards, typically presenting counts, averages, and trends over a defined time period.
Frequently asked questions
How is descriptive analytics different from prescriptive analytics?
Descriptive analytics summarizes what happened; prescriptive analytics goes further, recommending a specific action based on that data.
What is a common example of descriptive analytics in recruiting?
A monthly report showing total applications, hires, and average time-to-fill by department is a typical descriptive analytics report.
How BrightMove helps
BrightMove’s Wisdom analytics platform generates descriptive recruiting reports automatically from live ATS data. See BrightMove’s recruiting analytics.