Descriptive modeling is a type of statistical modeling that is used to describe the relationships between variables in a dataset. Descriptive models are typically used to summarize data or to predict future values.

##### What is descriptive modeling in data mining?

Descriptive modeling in data mining is the process of creating models that describe data. This can be done using a variety of techniques, including regression, decision trees, and neural networks. The goal of descriptive modeling is to create a model that accurately describes the data, without making any predictions about future data.

### What is descriptive business model?

A descriptive business model is a model that is used to describe the current state of a business. This type of model can be used to identify areas of improvement or potential areas of growth. Additionally, a descriptive business model can be used to benchmark a company against its competitors. What is the difference between predictive and descriptive? Predictive analytics uses historical data to make predictions about future events. Descriptive analytics uses data to describe what has already happened.

#### What is the main difference between descriptive and predictive analytics?

Descriptive analytics is all about understanding what has happened in the past. This type of analytics can be used to answer questions such as "how many products were sold last month?" or "what was the average customer satisfaction score last year?" Predictive analytics, on the other hand, is all about trying to understand what will happen in the future. This type of analytics can be used to answer questions such as "how many products are likely to be sold next month?" or "what is the probability that a customer will churn next month?" What is the main purpose of a descriptive model? Descriptive models are used to describe data. They can be used to summarize data, to find patterns in data, or to predict future data.