Spatial Data Science is a rapidly growing field that continues to expand its reach as industries recognize its value, with more enterprises maintaining Data Science and GIS departments, but still facing challenges in collaboration between these teams. The preferred language for Spatial Data Science operations is a topic of debate, with Python edges out R, but both have their advantages. The field faces a talent gap due to the lack of resources and qualified candidates, but academic and professional training programs are emerging to address this issue.