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With the development of the information age, cities provide a large amount ofdata that can be analyzed and utilized to facilitate the decision-makingprocess. Urban big data and analytics are particularly valuable in the analysisof business location decisions, providing insight and supporting informedchoices. By examining data relating to commercial locations, it becomespossible to analyze various spatial characteristics and derive the feasibilityof different locations. This analytical approach contributes to effectivedecision-making and the formulation of robust location strategies. Toillustrate this, the study focuses on Starbucks cafes in the Tianhe District ofGuangzhou City, China. Utilizing data visualization maps, the spatialdistribution characteristics and influencing factors of Starbucks locations areanalyzed. By examining the geographical coordinates of Starbucks, maindistribution characteristics are identified. Through this analysis, it exploresthe factors influencing the spatial layout of commercial store locations, usingStarbucks as a case study. The findings offer valuable insights into themanagement of industrial layout and the location strategies of commercialbusinesses in urban environments, opening avenues for further research anddevelopment in this field.

Leveraging Urban Big Data for Informed Business Location Decisions: A Case Study of Starbucks in Tianhe District, Guangzhou City