Power up your BigQuery analysis with Google's new geospatial datasets

Today at Google Cloud Next 25, we’re unveiling new geospatial analytics datasets and capabilities from Earth Engine and Google Maps Platform, integrated directly into BigQuery, Google’s unified data to AI platform. As BigQuery users, you know the power of data-driven insights, and these new capabilities will give you new dimensions of analysis, leveraging comprehensive geospatial data, to make better and faster decisions.

Geospatial analytics trends and challenges

The geospatial analytics market is rapidly evolving, driven by the emergence of powerful analytical tools, hyper-localization, and generative AI. Despite these advancements, organizations across industries face significant challenges in harnessing the full potential of geospatial analytics. For one, finding fresh, accurate, and comprehensive data in an analysis-ready format can be time-consuming and resource-intensive. Second, organizations face integration and analysis challenges, with disparate data sources introducing variability, requiring extensive transformation and preparation. Finally, scaling geospatial analytics programs can be difficult without specialized expertise and consistent approaches.

How our new geospatial capabilities address these challenges

Google Maps Platform is a trusted geospatial platform for over 10 million websites and apps, enriching the experiences for over 2 billion users. And for the last 15 years, Earth Engine has empowered data scientists with over 90 petabytes of satellite imagery and geospatial data. 

Customers want to access more insights from our up-to-date, comprehensive geospatial data, so they can make more informed business and sustainability decisions. That’s why for the first time, we're bringing select Google Maps Platform datasets, along with Earth Engine's datasets and analysis capabilities, directly into BigQuery. This means data analysts and decision-makers can now easily access and analyze fresh, comprehensive, and global geospatial data within the familiar BigQuery platform.

Here's what these new datasets and capabilities unlock:

• New insights, familiar tools: Tap into Google’s fresh, global geospatial data without needing advanced remote sensing or GIS expertise.

• Geospatial data integration: Integrate rich geospatial datasets with your existing data to unlock new insights that were previously difficult to obtain.

• Simplified data discovery and access: Say goodbye to time-consuming data wrangling. Access and analyze geospatial data as easily as your other BigQuery datasets.

For the first time, customers can now integrate analysis-ready imagery and datasets from Earth Engine, Places, and Street View into their existing BigQuery workflows using data clean rooms, extracting insights without sharing raw data.  To learn more about our new geospatial analytics datasets and capabilities, visit our new website.

Imagery Insights

Our first Imagery Insights dataset, available in Experimental for US, Canada, UK and Japan, helps you accelerate your infrastructure asset management by uniquely combining the global scale of Street View data, Vertex AI-powered analysis, and the scale of BigQuery. 

With this combination you can quickly identify and automatically assess the current conditions of your infrastructure assets like utility poles and road signs from Street View imagery, with the potential for many more attribute types to come. For example, if you are a city planner needing to determine your annual budget for road sign repairs, Imagery Insights can help you identify the exact number and locations of signs requiring attention using Street View imagery. This integration streamlines operations, optimizes workflows, and enables smarter, data-driven decisions for improved planning and operational efficiency. Express interest in testing Imagery Insights.

Places Insights

Places Insights provides access to aggregate insights from Google Maps data for more than 250 million businesses and places– refreshed monthly–to make more informed business decisions. With rich insights from this Places dataset, you can go beyond basic POI data like wheelchair accessibility and price level. You’ll access a more granular understanding of millions of businesses and points of interest like where most of the coffee shops are located in a zip code. 

Using BigQuery’s data clean room environment you can combine proprietary data with these insights from our Places data, to uncover deeper insights about locations.  Common use cases include identifying optimal store locations based on locations of complementary businesses, and a deeper understanding of local market dynamics. Express interest in testing Places Insights.

Roads Management Insights

Roads Management Insights helps Public Sector and Road Authorities improve road network efficiency and safety through data-driven traffic management. These insights stem from analysis of historical data to identify congestion patterns within your road networks, pinpoint potential causes of slowdowns, and take informed action. With access to real time monitoring, authorities can detect and respond to sudden speed drops, pinpoint the cause, and potentially reroute traffic within seconds of changes happening on the roads. Express interest in testing Roads Management Insights.

Earth Engine in BigQuery

Earth Engine in BigQuery brings the best of Earth Engine's geospatial raster data analytics directly into BigQuery. This feature makes advanced geospatial analysis of datasets derived from satellite imagery accessible to the SQL community–even if you don’t have remote sensing expertise. The ST_REGIONSTATS() function is a new BigQuery geography function that invokes Earth Engine to efficiently read and analyze geospatial raster data within a geographic area of interest. In addition, Earth Engine datasets in Analytics Hub now give you access to a growing collection of Earth Engine datasets directly within BigQuery, simplifying data discovery and access. Learn more here.

By using Google's geospatial analytics datasets within BigQuery, you can enable key business and environment decisions, such as how to optimize operations and maintenance of infrastructure, enable sustainable sourcing with global supply chain transparency, improve road safety and reduce congestion, and much more.

Visit our new website to discover how Google can help you unlock the power of geospatial data to drive better, faster business and sustainability decisions.

^{Note: in addition to new geospatial analytics datasets and capabilities from Google Maps Platform and Earth Engine, read here to learn more about Geospatial Reasoning, a new research effort announced at Cloud Next 25 by Google Research. Geospatial Reasoning will include new geospatial foundational models and a framework for building agentic workflows.}