Looker Studio es un servicio automático de visualización de informes y datos sin costo de Google Marketing Platform que se conecta a BigQuery y cientos de otras fuentes de datos. El servicio admite una variedad de tipos de campos geográficos y mapas de coropletas de polígonos de GEOGRAFÍA de BigQuery. Con la visualización basada en Google Maps, puedes visualizar tus datos geográficos y, además, interactuar con ellos como lo haces con Google Maps: desplazarte lateralmente, acercar la imagen, incluso visitar un lugar con Street View.
BigQuery Geo Viz es una herramienta web para la visualización de datos geoespaciales en BigQuery con las API de Google Maps. Puedes ejecutar una consulta en SQL y mostrar los resultados en un mapa interactivo. Las características de estilo flexible te permiten analizar y explorar tus datos.
BigQuery Geo Viz no es una herramienta de visualización de análisis de datos geoespaciales con todas las funciones. Geo Viz ofrece una forma rápida de visualizar los resultados de una consulta de análisis de datos geoespaciales en un mapa, una consulta a la vez.
Geo Viz es compatible con los datos de entrada geométricos (puntos, líneas y polígonos) que se recuperan como una columna GEOGRAPHY. Puedes usar las funciones de geografía de BigQuery para convertir la latitud y la longitud en GEOGRAPHY.
La cantidad de resultados que Geo Viz puede mostrar en un mapa está limitada por la memoria del navegador. Puedes disminuir la resolución y reducir el tamaño de los datos geoespaciales que se muestran en la consulta mediante la función ST_Simplify.
El navegador controla de forma local el análisis interactivo en tiempo real, que está sujeto a las capacidades del navegador.
Geo Viz admite el uso compartido de visualizaciones solo con usuarios autorizados a ejecutar consultas en el mismo proyecto de BigQuery.
Geo Viz no admite la descarga de una visualización para la edición sin conexión.
Google Earth Engine
También puedes visualizar los datos geoespaciales mediante Google Earth Engine. Para usar Earth Engine, exporta tus datos de BigQuery a Cloud Storage y, a continuación, impórtalos en Earth Engine. Puede usar las herramientas de Earth Engine para visualizar tus datos.
Si deseas obtener más información sobre cómo usar Google Earth Engine, consulta los siguientes instructivos:
Puedes realizar visualizaciones en notebooks de Jupyter mediante la extensión de GeoJSON.
Para usar esta extensión, tus datos geoespaciales deben estar en formato GeoJSON.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-03-06 (UTC)"],[[["\u003cp\u003eGeospatial analytics allows for the visualization of geographic location data through various tools.\u003c/p\u003e\n"],["\u003cp\u003eLooker Studio offers a no-cost, self-serve reporting and data visualization service with features like geographic field types, choropleth maps, and Google Maps-based visualization.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery Geo Viz is a lightweight web tool that enables the visualization of geospatial data from BigQuery via interactive maps but is limited in terms of real-time analysis and supported inputs.\u003c/p\u003e\n"],["\u003cp\u003eGoogle Earth Engine provides another avenue for visualizing geospatial data by exporting data to Cloud Storage and using the Earth Engine's tools.\u003c/p\u003e\n"],["\u003cp\u003eJupyter notebooks, with the GeoJSON extension, can be utilized for visualizing geospatial data in GeoJSON format.\u003c/p\u003e\n"]]],[],null,["# Visualize geospatial data\n=========================\n\nGeospatial analytics lets you visualize geographic location data by\nusing the following:\n\n- [BigQuery Studio](#bigquery_studio)\n- [Looker Studio](#data_studio)\n- [BigQuery Geo Viz](#geo_viz)\n- [Colab notebooks](#colab)\n- [Google Earth Engine](#google_earth)\n\nBigQuery Studio\n---------------\n\n|\n| **Preview**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n| **Note:** To request support or provide feedback for this feature, email [bigquery-earthengine-preview-support@google.com](mailto:bigquery-earthengine-preview-support@google.com).\n\nBigQuery Studio offers an integrated geography data viewer. When your query\nresults contain one or more `GEOGRAPHY` type columns, you can view the results\nin an interactive map.\nTo view the map, in the **Query results** pane, click the **Visualization** tab.\n\nVisualization in BigQuery is ideal for quick inspections and\niterative query development. You can visually confirm data alignment with\nexpectations, identify outliers, and assess the correctness of your spatial\ndata. It's also useful for ad hoc analysis to explore results and derive\nimmediate conclusions from geospatial queries.\n\nTo see an example of how to use the integrated geography viewer, see\n[Get started with geospatial analytics](/bigquery/docs/geospatial-get-started).\n\n### BigQuery Studio limitations\n\n- You can only visualize one `GEOGRAPHY` column at a time.\n- Performance is subject to browser capabilities and isn't intended for rendering extremely large or complex datasets. BigQuery renders up to approximately one million vertices, 20,000 rows, or 128 MB of results.\n\nLooker Studio\n-------------\n\nLooker Studio is a no-cost, self-serve reporting and data visualization\nservice from Google Marketing Platform that connects to BigQuery\nand hundreds of other data sources. The service includes support for a variety\nof [geographic field types](https://support.google.com/looker-studio/answer/9843174)\nand [choropleth maps](https://en.wikipedia.org/wiki/Choropleth_map) of\nBigQuery `GEOGRAPHY` polygons. With\n[Google Maps-based visualization](https://support.google.com/looker-studio/answer/9713352),\nyou can visualize and interact with your geographic data just as you do with\nGoogle Maps: pan around, zoom in, and pop into Street View.\n\nFor a walkthrough of geospatial analytics in Looker Studio, see\n[Visualize BigQuery `GEOGRAPHY` polygons with Looker Studio](https://support.google.com/looker-studio/answer/10502383).\n\nBigQuery Geo Viz\n----------------\n\nBigQuery Geo Viz is a web tool for visualization of geospatial\ndata in BigQuery using Google Maps APIs. You can run a SQL query\nand display the results on an interactive map. Flexible styling features let\nyou analyze and explore your data.\n\nBigQuery Geo Viz is not a fully featured geospatial analytics\nvisualization tool. Geo Viz is a lightweight way to visualize the results of a\ngeospatial analytics query on a map, one query at a time.\n\nTo see an example of using Geo Viz to visualize geospatial data, see\n[Get started with geospatial analytics](/bigquery/docs/geospatial-get-started).\n\nTo explore Geo Viz, go to the Geo Viz web tool:\n\n[Go to Geo Viz](https://bigquerygeoviz.appspot.com/)\n\n### Geo Viz limitations\n\n- Geo Viz supports geometry inputs (points, lines, and polygons) that are retrieved as a `GEOGRAPHY` column. You can use BigQuery's geography functions to convert latitude and longitude to `GEOGRAPHY`.\n- 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 `ST_Simplify` function.\n- Real-time, interactive analysis is handled locally by your browser and is subject to your browser's capabilities.\n- Geo Viz supports sharing visualizations only with users authorized to execute queries in the same BigQuery project.\n- Geo Viz does not support downloading a visualization for offline editing.\n\nColab notebooks\n---------------\n\nYou can also perform geospatial visualizations in Colab\nnotebooks. For a tutorial on building a Colab notebook to\nvisualize data, see [BigQuery geospatial visualization in Colab](/bigquery/docs/geospatial-visualize-colab).\n\nTo view and run a prebuilt notebook, see [BigQuery geospatial visualization in Colab](https://github.com/GoogleCloudPlatform/bigquery-utils/blob/master/notebooks/bigquery_geospatial_visualization.ipynb) in GitHub.\n\nGoogle Earth Engine\n-------------------\n\nYou can also visualize geospatial data using Google Earth Engine. To use\nGoogle Earth Engine, export your BigQuery data to Cloud Storage\nand then import it into Google Earth Engine. You can use the Google Earth Engine tools\nto visualize your data.\n\nFor more information on using Google Earth Engine, see the:\n\n- [Google Earth Engine developer's guide](https://developers.google.com/earth-engine/)\n- [Google Earth Engine API tutorials](https://developers.google.com/earth-engine/tutorials)"]]
