CARTO Analytics Toolbox has introduced three new spatial SQL functions to analyze point data in BigQuery, extending its geospatial capabilities. The functions include k-nearest neighbors (KNN) to find closest points, Local Outlier Factor (LOF) to identify spatial outliers, and G-function to inspect the spatial distribution of point data. These functions can be used for various use cases such as analyzing relationships between locations like Points of Interest or identifying clusters in location-based data. The KNN function can also be leveraged to spot spatial outliers by computing an index called the Local Outlier Factor (LOF). The G-function calculates the cumulative frequency distribution of 1-order nearest neighbor distances, allowing for the detection of patterns such as random, clustered, or regular distributions. These advanced analytical capabilities are now available in CARTO Analytics Toolbox for BigQuery Snowflake Redshift and Databricks.