Analysis and Application of Retail Commodity Consumption Situation

In the background of the continuous development of information technology and big data, retail enterprises have accumulated massive data. In order to fully use these data and intuitively show the retail market sales situation, this paper proposes a system that combines spatial-temporal grid division, knowledge graph implicit relationship mining and market situation visualization technology. This system firstly associates and integrates external consumer market data with internal sales data through spatial-temporal grid division technology to form a basic data source with time series and geographic space characteristics. Then, the knowledge graph technology is used to mine the implicit relationship among commodities, markets and consumers (CMC). Finally, this paper adopts visualization technology to construct a system that reflects the changes of the retail market and the internal connection among CMC in the field of commodity consumption. The system can provide technical support for big data mining and multi-angle visualization analysis of the retail commodity market.