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UID:pretalx-foss4g-2024-SSAKBD@talks.staging.osgeo.org
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DESCRIPTION:The modern Python geospatial stack encompasses several tools an
 d libraries that allow scientists and developers to write more efficient a
 nd scalable data science workflows\, from data access and preparation\, to
  analysis and visualization. It provides a great ecosystem for reading and
  writing cloud-optimized and chunked data formats\, accessing data catalog
 s\, handling labeled N-dimensional arrays\, parallel and distributed compu
 ting\, statistical analysis\, machine learning\, and interactive computing
  and plotting.\n\nAs data scientists increasingly work in teams and tackle
  bigger and more complex problems\, there is a growing need for collaborat
 ive platforms that can support sophisticated workflows and large-scale dat
 a processing. However\, platforms for effective collaboration still have s
 ignificant challenges\, including deployment\, configuration\, graceful sc
 aling\, and environment and dependency management. Addressing these challe
 nges is not trivial and it often requires some DevOps expertise.\n\nIn thi
 s talk\, we’ll introduce Nebari\, a cloud-based open source data science
  platform built on top of Kubernetes\, Dask and the Jupyter ecosystem. Neb
 ari enables organizations to quickly deploy a collaborative platform on an
 y of the major cloud providers. Once deployed\, teams can easily access si
 ngle-user Jupyter Notebook and VS Code servers from their web browsers and
  start writing and running reproducible and scalable geospatial data scien
 ce workflows. Integrated with conda-store and Dask\, it provides users not
  only the possibility to build\, share and access conda environments from 
 their servers\, but also to launch short-lived clusters to handle their co
 mpute-intensive tasks.\n\nWe’ll demonstrate how Nebari can be leveraged 
 to develop compute and data intensive applications in the cloud using pack
 ages from the modern Python geospatial stack. By the end\, we hope to equi
 p organizations with the tools and knowledge to promote better and more ef
 fective collaboration in geospatial data science. Organizations can choose
  to adopt Nebari as an out-of-the box platform for their teams\, or use it
  as a blueprint for developing a custom platform built on top of open sour
 ce libraries.
DTSTAMP:20260510T205610Z
LOCATION:Room II
SUMMARY:Modern Geospatial Data Science in the Cloud with Nebari - Marcelo V
 illa
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/SSAKBD/
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