Data Science: Descriptive Analytics (Definitions)

"The practice of reporting what has happened, analyzing contributing data to determine why it happened, and monitoring new data to determine what is happening now. Also known as reporting and business intelligence." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"If you are using charts and graphs or time series plots to study the demand or the sales patterns, or the trend for the stock market you are using descriptive analytics. Also, calculating statistics from the data such as, the mean, variance, median, or percentiles are all examples of descriptive analytics." (Amar Sahay, "Business Analytics" Vol. I, 2018)

"The simplest form of data analytics, in which historical data is collated and summarized in a user-friendly format, providing an understanding of what has previously happened." (Board International)

"Descriptive analytics is a form of data analytics that looks at data statistically to tell you what happened in the past. It helps a business understand how it is performing by providing context that will aid stakeholders in interpreting information." (Logi Analytics) [source]

"Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis." (Techtarget) [source]