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hands-on lab

Importing and Exporting Geography Data with BigQuery

Difficulty: Beginner

Duration: Up to 1 hour

Students: 70

Rating: 4.2/5

On average, students complete this lab in20m

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Description

This lab introduces the special GEOGRAPHY data type in Google Cloud Platform’s BigQuery GIS serverless data warehouse tool. The lab walks the user through the spatial constructor functions which allow the user to create GEOGRAPHY objects, including points, linestrings, and polygons. The final section covers how users can export GEOGRAPHY objects into other data formats, such as GeoJSON.

Learning Objectives

Upon completion of this lab you will be able to:

Interact with BigQuery datasets within Jupyter notebooks
Convert geospatial data into a BigQuery GIS GEOGRAPHY data object
Export BigQuery GIS GEOGRAPHY objects into other formats

Intended Audience

This lab is intended for:

GIS engineers
Data engineers dealing with location-based data
Developers looking to leverage geospatial information

Prerequisites

You should possess:

Basic understanding of relational databases and ANSI SQL
Basic understanding of Python

Updates

August 20th, 2025 - Resvoled issue connecting to the lab's notebook

May 28th, 2025 - Migrated lab environment and updated screenshots to reflect the latest UI

August 7th, 2024 - Added password protection to notebook

Covered topics

Google Cloud Platform

Analytics for Google

Databases for Google

Storage for Google

NoSQL for Google

Big Data for Google

Hands-on Lab UUID

Lab steps

0 of 2 steps completed.Use arrow keys to navigate between steps. Press Enter to go to a step if available.

Signing In to the Google Cloud Console
Starting the Lab's Google Cloud Hosted JupyterLab Notebook

Lab Rules

Lab rules apply