hands-on lab

Machine Learning and BigQuery GIS

Intermediate
Up to 1h
86
5/5
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Lab description

This lab demonstrates how to perform a clustering analysis in BigQuery GIS using Python and Jupyter notebooks. The lab leverages the built-in DBScan clustering function in BigQuery GIS to cluster street trees in San Francisco from the Google public datasets. It also shows how to analyze the cluster results using the pandas library within Python.

Learning Objectives

Upon completion of this lab you will be able to:

  • Interact with BigQuery GIS datasets within Jupyter notebooks
  • Perform a clustering analysis on GEOGRAPHY data
  • Use pandas to analyze cluster analysis results

Intended Audience

This lab is intended for:

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

Prerequisites

You should possess:

  • Basic understanding of relational databases and ANSI SQL
  • Basic understanding of Python
  • Familiarity with BigQuery GIS's GEOGRAPHY datatype
About the author
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Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity.  With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing  decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.

Covered topics
Lab steps
Starting the Lab's Jupyter Notebook in Google Cloud