Spatial Data Simplified: Introducing Data Observatory 2.0` introduces the concept of spatial data analysis, which relies heavily on access to relevant data. However, gathering and cleaning data is often time-consuming, taking up to 80% of a Data Scientist's total analysis time. This is particularly challenging for Spatial Data Science, where data sources are highly varied. CARTO aims to improve efficiency by releasing Data Observatory 2.0, a private beta version that simplifies access to public data and commercial datasets, enables easier data joins through a common geographic base, and streamlines Data Science workflows. The new platform addresses three key issues: discovery, licensing, and ETL/joining, reducing the time spent on these tasks from months to weeks. By reducing the cost of accessing and using data, Data Observatory 2.0 aims to increase the use of data, ultimately leading to a continuous virtuous cycle of reduced data costs and increased usage. The platform is designed to support Data Scientists in Python Notebooks, providing an integrated experience for managing data discovery, purchase, and access without leaving their analysis environment.