- Stay within resource usage requirements.
- Do not engage in or encourage activity that is illegal.
- Do not engage in cryptocurrency mining.
Ready for the real environment experience?
This lab will teach you how to create maps from geospatial data using the GeoJSON extension for JupyterLabs. The first section of the lab walks through building a map of New York City landmarks, building up from a single geospatial point, then creating a feature collection and finally adding points to the existing feature collection. The second section uses Google’s zip code public dataset to convert BigQuery
GEOGRAPHY objects to GeoJSON format and map geospatial polygons.
Upon completion of this lab you will be able to:
- Use the GeoJSON extension to JupyterLabs to map geospatial data
- Map GeoJSON objects in Jupyter notebooks
- Interact with BigQuery GIS datasets within Jupyter notebooks
- Map geospatial data from BigQuery GIS's
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
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.