Giulia Carella is a Data Scientist at CARTO. She holds a PhD in Applied Statistics and has experience in the development and application of statistics and machine learning methods for spatio-temporal data, with applications ranging from climate science to spatial demography.
The Retail module in our Analytics Toolbox for Google BigQuery now includes Twin Areas analysis, an essential tool in Site Selection analytics. Learn more.
We are pleased to introduce 3 new functions for point data analysis in our Analytics Toolbox for Google Cloud BigQuery: K-nearest neighbors, Local Outlier Factor, & G-function
We are pleased to announce that the CARTO Analytics Toolbox for BigQuery now supports the Geographically Weighted Regression method–read about its usage.
Discover how Point of Interest (POI) data can be used to uncover site selection strategies of leading brands in the US including McDonald's, Starbucks, & Subway
A detailed geospatial analysis of how changes & regional disparity in human mobility during the COVID-19 lockdown can be related to socioeconomic indicators.
