Data Connect

Data Connect: North America - Geolocation applications with KNIME (Hybrid)

January 25, 2023 - Hybrid
Data Connect: North America (Hybrid)

Join the next edition of Data Connect: North America live in Boston. This event will be hosted in Hybrid mode.

Talk 1 - Organizations around the world depend on geospatial data for site selection, supply chain optimization, environment management, fraud detection and more. Historically, accessing and analyzing this invaluable data, however, has required niche expertise, demanding deep experience with a wide array of data sources and libraries, as well as coding skills.

Harvard’s Center for Geographic Analysis & KNIME have teamed up to enable non-expert users to unlock the potential of geospatial data by accessing, blending and analyzing it through a no-code environment. This session will cover how Harvard CGA and KNIME are working together to provide users not only a dedicated geospatial analysis extension but also reusable and reproducible data and blueprints to effortlessly use and adapt to their needs.

Talk 2 - One powerful feature of KNIME Analytics Platform is the possibility to easily blend data of different types and from various data sources. Another strength is its capability of easily creating interactive Data Apps to enable a broad user group to get insights from their data without seeing the complexity of the underlying workflow . This presentation will show how to build such a Data App which will take you around the world. Follow this journey and learn how to visualize geospatial data in KNIME v4.7 in a fully codeless fashion with the help of the Geospatial Analytics Extension.


How do I join the KNIME Data Connect?

This event will be hosted in Hybrid mode. Join the next edition of Data Connect: North America live in Boston. Or online on Gather Town, you will receive a link to join the interactive session with your registration confirmation.

Where do I find the latest version of KNIME Analytics Platform?

Download the latest free, open source version of KNIME here:

What other resources will help me to get started in KNIME?
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