Question: How can I easily match and merge geospatial data from various sources without worrying about address inconsistencies?

If you're looking for a simple way to match and merge geospatial data from different sources without worrying about address matching problems, Placekey is a good option. It provides a universal place identifier system that sidesteps address matching problems by providing a single identifier for any address. Placekey uses a standard format that combines location name, street address, city, state, postal code, and country to produce a single identifier. The service offers a free API for adding Placekeys to addresses, POIs, or latitude and longitude pairs, and for matching addresses and POIs, deduping and entity resolution.

Another good option is CARTO, a cloud-native location intelligence platform that lets you analyze, visualize and build applications with spatial data at large scale. CARTO's platform can be used in conjunction with native analysis and visualization tools on cloud data warehousing services like BigQuery, Snowflake, Redshift and Azure. It comes with an easy-to-use drag-and-drop interface, 100+ pre-built analysis components and built-in GenAI abilities, so it's a good option for companies that want to tap into spatial analytics and visualization.

If you need a full-featured GIS mapping and spatial analytics tool, Esri has a powerful platform that marries location analytics and machine learning. Esri's platform includes 3D visualization, location intelligence, GIS mapping and spatial analysis, and is used in many industries and use cases. It comes with a 21-day free trial, training, developer tools and a community, so it's a good option for real-time decision-making and predictive modeling.