Flower model is a widely used multidimensional data analysis method, which helps people understand complex information with vivid image and intuitive structure. In this model, the core idea is to facilitate the discovery of relationships and patterns between data by visualizing the data in the form of flowers.

In the flower model, each flower represents a data set, while the petals symbolize different dimensions or properties of the data. For example, if we take the sales data of an e-commerce company as an example, the center of each flower may be a certain product, and the petals can be sales, customer reviews, inventory and other indicators related to that product. In this way, analysts can visually see which products are performing better and which products are receiving more positive customer feedback, allowing them to make more informed decisions.

In addition to data visualization, the flower model also has a certain level of hierarchy. The color, size, or shape of the petals can be used to indicate the weight or importance of different data dimensions. For example, if a particular petal is particularly prominent, it may indicate the importance of that dimension to the overall data analysis. This hierarchical design enables users to quickly grasp key elements in the face of complex data, avoiding redundancy and confusion of information.

In practical application, flower model is not only suitable for sales data analysis, but also suitable for market research, customer segmentation, risk assessment and other fields. With the development of big data technology, more and more enterprises have begun to use flower models to optimize data analysis processes to improve business efficiency and decision accuracy.