Descriptive Analytics

Descriptive Analytics is the process of analyzing historical data to understand what has happened in a business in the past. Like looking at a photo album to recall events, descriptive analytics examines data such as sales numbers, expenses, or customer behavior to provide insight into business performance over a certain period. It’s the most common type of data analytics, and it lays the foundation for more advanced types of analysis, like predictive or prescriptive analytics.

Using different tools and techniques, like data mining or data visualization, descriptive analytics helps summarize large datasets to pinpoint trends and patterns. For example, it can tell a business how many products were sold in the last quarter or what the average customer spends in a year. This kind of information is essential because it helps businesses paint a picture of their operations and customer interactions, highlighting successes and identifying areas that may need improvement.

By offering a clear view of past performance, descriptive analytics provides businesses with the context they need to plan for the future. It answers the ‘what happened?’ question, giving companies the factual evidence they need to understand their current position and helping them to make informed, data-driven decisions moving forward.