What Is Descriptive Analytics?

Descriptive analytics is like taking a photo of a moment in time to capture what has happened. It involves looking at past data to understand trends, patterns, or insights about that period. Think of it as creating a detailed report card that shows how things have been performing.

Here’s a simple way to understand it:

1. The Story of Past Data: Descriptive analytics tells the story of what has happened in the past, like summarizing the events of a party you've attended.
2. Overview and Summary: It provides an overview or summary of this past data, similar to how a movie recap gives you a rundown of the plot.
3. Identifying Trends: Just like noticing that you tend to spend more money on weekends, descriptive analytics helps identify trends in data.
4. Understanding Performance: It's like checking the scoreboard after a game to see how each player performed.
5. Visual Representation: Descriptive analytics often involves charts and graphs, making it easier to see what’s going on, like a photo album giving a visual story of your last vacation.
6. Basis for Further Analysis: While it doesn’t predict the future or explain why things happened, it provides the foundation for more advanced types of analysis, like diagnostic, predictive, or prescriptive analytics.

In essence, descriptive analytics is about looking back at historical data to understand what has happened, giving you a clear picture of past performance, trends, and patterns. It's a crucial first step in data analysis, setting the stage for deeper insights and decision-making.