Goal

Think only geographers need geospatial data? Think again.

Customer addresses, branch locations, delivery routes, they all offer profound value by providing transformative insights beyond an organization's internal data assets. This workshop addresses the unique challenges posed by geospatial data and empowers participants to unlock its untapped potential, enabling informed decision-making within their organizations.

In-depth

Geospatial Data Science is the discipline of distilling insights from any source of data that comes with a spatial component. Enriching internal data sources with the geo component is key to understanding where and why things happen at certain locations.

The advent of new and predominantly public geospatial datasets presents unique opportunities to uncover valuable insights in different applications, including supply chain management and logistics, personalized real-estate management, marketing campaigns, etc. However, the analysis of geo data can appear daunting and time-consuming at first, leading to many companies not leveraging its full potential.

In this workshop, we will examine the typical challenges geospatial data can pose and provide practical solutions to overcome them. Participants will be introduced to the fundamental concepts of geospatial data science and guided through a data pipeline for storing, manipulating and visualizing geodata. In addition to the technical know-how, we will showcase the wealth of geospatial open-source data that is made available, among others, by the Swiss government. Understanding where to find this data and how to process it can be demanding, but it is essential knowledge that can enable participants to create value from freely accessible datasets.

Target Audience

This workshop targets data professionals (data scientists, data engineers, data analysts) interested in working with geo-data and the related state-of-the-art toolset in Python. Basic knowledge of Python (dataframes and Pandas operations) is desirable.