What type of analysis can be performed using geospatial data types in BigQuery?

Geospatial analysis is specifically designed to work with geospatial data types, allowing users to perform various operations and analyses that consider the geographic context of the data. In BigQuery, geospatial data types enable functionalities such as calculating distances, determining intersections between geographical features, and managing spatial relationships among different geospatial objects. These capabilities make geospatial analysis particularly powerful for tasks involving maps, location-based services, urban planning, environmental monitoring, and other applications that require an understanding of spatial relationships and patterns.

While statistical analysis, time series analysis, and predictive analysis can certainly be performed in BigQuery using various data types and approaches, they do not specifically leverage the unique capabilities offered by geospatial data types. Instead, they focus on numerical data and trends over time or predicting future outcomes based on historical data. The essence of geospatial analysis lies in its strong focus on spatial attributes, utilizing the functionality provided by geospatial data types to generate insights tied closely to geographic locations.