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# Big Data User Group

Serve as a community resource for advising big data and data science related software projects on techniques and best practices for integrating with Kubernetes. Represents the concerns of users from big data communities to Kubernetes for the purposes of driving new features and other enhancements, based on big data use cases.

## Meetings
*Joining the [mailing list](https://groups.google.com/forum/#!forum/kubernetes-ug-big-data) for the group will typically add invites for the following meetings to your calendar.*
* Regular User Group Meeting: [Wednesdays at 18:00 UTC](https://zoom.us/my/ug.big.data) (biweekly). [Convert to your timezone](http://www.thetimezoneconverter.com/?t=18:00&tz=UTC).
  * [Meeting notes and Agenda](https://docs.google.com/document/d/1pnF38NF6N5eM8DlK088XUW85Vms4V2uTsGZvSp8MNIA/edit).
  * [Meeting recordings](https://docs.google.com/document/d/1pnF38NF6N5eM8DlK088XUW85Vms4V2uTsGZvSp8MNIA/edit).

## Organizers

* Erik Erlandson (**[@erikerlandson](https://github.com/erikerlandson)**), Red Hat
* Anirudh Ramanathan (**[@foxish](https://github.com/foxish)**), Rockset
* Yinan Li (**[@liyinan926](https://github.com/liyinan926)**), Google

## Contact
- Slack: [#ug-big-data](https://kubernetes.slack.com/messages/ug-big-data)
- [Mailing list](https://groups.google.com/forum/#!forum/kubernetes-ug-big-data)
- [Open Community Issues/PRs](https://github.com/kubernetes/community/labels/ug%2Fbig-data)
- GitHub Teams:
    - [@kubernetes/ug-big-data](https://github.com/orgs/kubernetes/teams/ug-big-data) - General Discussion
- Steering Committee Liaison: Tim Pepper (**[@tpepper](https://github.com/tpepper)**)
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### Goals

- Promoting best practices for Kubernetes integrations
- Advising big data communities on Kubernetes features
- Shepherding issues and pull requests from community members
- Hosting demos and discussions of big data integrations for Kubernetes

### Non Goals

- Promoting or otherwise advocating for any specific big data project
- Software and tooling communities that have no intersection with data science or big data

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