Context and issues
A Colombian development bank wanted to analyse financial inclusion in the country, by geolocating cash-in cash-out agents and cross-analysing this data with population density layers, economic activity layers, and other geospatial dimensions to better inform policy making.
Masae designed and facilitated in Spanish a hands-on, in-person training that included:
Web-scrapping of bank institutions websites
Geocoding of street addresses
Geospatial visualization with QGIS
Geospatial data processing with Python
Code and data management principles and tips
Thanks to this training and regular follow-up support from Masae, the bank's team became autonomous in web scraping, geocoding, and many other geospatial analysis tools.