Satellites have long been used to measure economic indicators that could not be analyzed due to poor data quality or the lack of frequent measurements. For example, researchers in several seminal works investigate economic development, air pollution, and housing quality using satellite data from visible and invisible light spectra. In recent years, however, not only have economists become interested in using satellite images, but actors in the financial sector are also increasingly using satellite data to improve returns. From quickly recognizable applications in the commodity markets to measuring trade movements and forecasting quarterly earnings by counting vehicles in parking lots of retailers, satellite imagery is now a commonly used source for information in finance. This rise in popularity was made possible by the search for "alternative data" in the financial sector. As resolution improved and artificial intelligence helped to autonomously identify objects, satellite images became a new alternative data source. Based on academic literature, earning calls, and partnership announcements, this paper provides an overview of the use cases for satellite data in financial markets. The paper thus offers practitioners' and researchers' best practices and gives an overview of the available and utilized data sources and satellite constellations. Startups that analyze satellite imagery or even build new constellations could also benefit from this insight into the data and analyses that interest the solvent players of the financial sector.