Ready for the real environment experience?
This lab will teach you how to perform spatial measurements and spatial transformations in BigQuery GIS using Python and Jupyter notebooks. The lab uses New York City landmark geospatial points to demonstrate the distance measurement function within BigQuery GIS and Google public census places data to demonstrate the area measurement function on a geospatial polygon. Spatial transformation functions are demonstrated by calculating the centroid of geospatial polygons from the Google zip code public data and combining single geospatial points into multipoint
GEOGRAPHY objects using the aggregate union transformation function from the Google New York tree census public data.
Upon completion of this lab you will be able to:
- Interact with BigQuery GIS datasets within Jupyter notebooks
- Perform spatial measurements on
- Perform spatial transformations on
This lab is intended for:
- GIS engineers
- Data engineers dealing with location-based data
- Developers looking to leverage geospatial information
You should possess:
- Basic understanding of relational databases and ANSI SQL
- Basic understanding of Python
- Familiarity with BigQuery GIS's
GEOGRAPHYdatatype is beneficial but not required
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.