Spatial Analysis and Visualization with BigQuery GIS

This course 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.

Description
This course 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 course is ideal for you!

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 course 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 course, you should have basic familiarity with SQL, Python, and cloud computing, ideally Google Cloud Platform.