Welcome to the Building Geospatial Multi-Lay Apps with Snowflake and Streamlit quickstart. Today you will learn how to analyse and transform geospatial data in Snowflake. You will be using Ordnance Survey open datasets available on the marketplace as well as the worldwide open overture buildings dataset provided by CARTO.

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This is a progressive learning experience from viewing points on a mapk right through to building a multi layer app - which pulls together buildings with unique property reference numbers, the road network and urban extents.

You will be covering:

Thoughout the experience, you will demonstrate the concepts with Snowflake Notebooks and Streamlit.

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Structure of the session

The Lab consists of three notebooks and two Streamlit applications.

What You Will Learn

What You'll Build

Prerequisites

Open up a new SQL worksheet and run the following commands. To open up a new SQL worksheet, select Projects » Worksheets, then click the blue plus button and select SQL worksheet.

CREATE DATABASE IF NOT EXISTS ANALYSE_LOCATION_DATA;

CREATE WAREHOUSE IF NOT EXISTS LOCATION_ANALYTICS;

CREATE SCHEMA IF NOT EXISTS NOTEBOOK;
CREATE SCHEMA IF NOT EXISTS STREAMLIT;
CREATE SCHEMA IF NOT EXISTS DEFAULT_SCHEMA;

Ordnance Survey Datasets

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Carto Datasets - Obtain the following datasets from the marketplace

This dataset provides sample building polygons all over the world.

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Are you ready to start learning about location data in Snowflake?

This tutorial will take you through how you can use location data to perform spatial calculations, joins, and visualise the data using the popular Pydeck python package. We will be using the freely available datasets which you have now installed to step through examples of how geospatial data can be handled.

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This app gives you an example of how you can bring all these datasets together to form a multi layered mapping visual.

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Conclusion

Congratulations on completing the Building Geospatial Multi-Layer Apps with Snowflake and Streamlit Quickstart! Throughout this session, you've explored how Snowflake can be used to analyze and transform geospatial data, combining multiple datasets to generate valuable insights.

What You Learned

Next Steps

With this foundational knowledge, you can extend your analyses by:

We hope this hands-on lab has provided you with the confidence and skills to apply geospatial analytics in your own projects. Happy analyzing! 🚀

Related Resources

Source code

Further Related Material