Geographic Information Systems

This lesson is now outdated.

This lesson explores geographic information system (GIS) topics and how to query and analyze GIS data within the database environment of BigQuery GIS. We'll start off by defining what GIS is, discussing some key GIS concepts, and introducing some common GIS data types.

We'll then move on to common types of maps and introduce the concept of map projections. You'll get an introduction to Google's BigQuery tool, and finally, we'll put all these topics together and look at how you can perform analysis and visualization using SQL and Python in conjunction with BigQuery GIS.

If you have a use case analyzing and mapping geospatial data or anticipate one in the future, especially if your data is in a relational format (or already in BigQuery), then this lesson is ideal for you!

Please feel free to contact us at support@cloudacademy.com with any feedback you may have related to this lesson. 

Learning Objectives

• Learn about Google BigQuery GIS and its concepts, as well as common GIS data formats
• Understand the common types of maps and the concept of map projections
• Learn about spatial query functionality and spatial visualization
• Understand how BigQuery GIS can be integrated with Python

Intended Audience

This lesson is intended for anyone who wants to:

• Leverage BigQuery GIS for their geospatial analytics needs
• Learn how to visualize data on maps

Prerequisites

To get the most out of this lesson, you should have basic familiarity with SQL, Python, and cloud computing, ideally Google Cloud Platform.