Managing Spatiotemporal Data Fusion at Scale Using The Geodesic Platform

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Topic: Managing Spatiotemporal Data Fusion at Scale Using The Geodesic Platform

Speaker: Daniel Wilson, CTO at SeerAI

Daniel Wilson is the CTO at SeerAI who has spent his career applying novel advanced analytics techniques such as Artificial Intelligence, Machine Learning, and Big Data to real world problems. After tackling some of the US Intelligence Community's toughest geospatial data challenges, Daniel transitioned to lead a team at Esri focused on developing next generation geospatial AI capabilities, before co-founding SeerAI.

Abstract:
Working with spatiotemporal data such as satellite imagery, weather data, location data, and more requires care and significant processing power. The numerous forms that it can take means that data ingest/ETL must be very carefully written, executed, and tracked. When building sophisticated Data Fusion models using multiple disparate datasets, the challenges soon become overwhelming. Geodesic, SeerAI’s cloud native spatiotemporal data fusion platform, makes working with planetary scale spatiotemporal data orders of magnitude simpler, and Pachyderm makes it repeatable and headache free. In this talk, we discuss how we at SeerAI leverage Pachyderm to ensure full traceability on our decentralized spatiotemporal data lake as well as reliable tracking and management of large-scale machine learning pipelines.

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