You can visualize BigQuery GIS data by using:
- BigQuery Geo Viz
- Google Earth Engine
- Jupyter notebooks (via the GeoJSON extension)
Currently, BigQuery GIS visualizations are not supported by Google Data Studio.
BigQuery Geo Viz
BigQuery Geo Viz is a web tool for visualization of geospatial data in BigQuery using Google Maps APIs. You can run a SQL query and display the results on an interactive map. Flexible styling features allow you to analyze and explore your data.
BigQuery Geo Viz is not a fully-featured BigQuery GIS visualization tool. Geo Viz is a lightweight way to visualize the results of a BigQuery GIS query on a map, one query at a time.
To see an example of using Geo Viz to visualize BigQuery GIS data, go to Getting started with BigQuery GIS for data analysts.
To explore Geo Viz, go to BigQuery Geo Viz web tool.
Geo Viz limitations
- Geo Viz supports geometry inputs (points, lines, and polygons) that are
retrieved as a
GEOGRAPHYcolumn. You can use BigQuery's geography functions to convert latitude and longitude to
- The number of results that Geo Viz can display on a map is limited by browser
memory. You can lower the resolution and reduce size of geospatial data
returned from the query by using
- Real-time, interactive analysis is handled locally by your browser and is subject to your browser's capabilities.
- Geo Viz supports sharing visualizations only with users authorized to execute queries in the same BigQuery project.
- Geo Viz does not support downloading a visualization for offline editing.
Google Earth Engine
You can also visualize BigQuery GIS data using Google Earth Engine. To use Earth Engine, export your BigQuery data to Cloud Storage and then import it into Earth Engine. You can use the Earth Engine tools to visualize your data.
For more information on using Google Earth Engine, see the:
You can perform visualizations in Jupyter notebooks by using the GeoJSON extension. To use this extension, your BigQuery GIS data must be in GeoJSON format.
For more information, see the GeoJSON extension in GitHub.
For a tutorial on using Jupyter notebooks to visualize data, see Visualizing BigQuery data in a Jupyter notebook.