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docs: include license in the readme (#2559)
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Harshal Sheth
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README.md
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README.md
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<!--HOSTED_DOCS_ONLY
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import ThemedImage from '@theme/ThemedImage';
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import useBaseUrl from '@docusaurus/useBaseUrl';
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@ -54,25 +53,27 @@ HOSTED_DOCS_ONLY-->
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---
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> 📣 Next DataHub town hall meeting on May 27th, 9am-10am PDT ([convert to your local time](https://greenwichmeantime.com/time/to/pacific-local/))
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>
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> - Topic Proposals: [submit here](https://docs.google.com/forms/d/1v2ynbAXjJlqY97xE_X1DAntNrXDznOFiNfryUkMPtkI/)
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> - Signup to get a calendar invite: [here](https://docs.google.com/forms/d/1r9bObXKS3tgKpISqqO3rw4yQog5zwuaFxg8IrJGUbvQ/)
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> - Town-hall Zoom link: [zoom.datahubproject.io](https://zoom.datahubproject.io)
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> - [Meeting details](docs/townhalls.md) & [past recordings](docs/townhall-history.md)
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> ✨ Latest Update:
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> ✨ Latest Update:
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>
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> - Monthly project update: [Apr 2021 Edition](https://medium.com/datahub-project/linkedin-datahub-project-updates-2b0d26066b8f?source=friends_link&sk=686c47219ed294e0838ae3e2fe29084d).
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> - Unleashing Excellent DataOps with LinkedIn DataHub: [DataOps Unleashed Talk](https://www.youtube.com/watch?v=ccsIKK9nVxk).
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> - Latest blog post [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained) @ LinkedIn Engineering Blog.
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> - Latest blog post [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained) @ LinkedIn Engineering Blog.
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> - We've released v0.7.1. You can find release notes [here](https://github.com/linkedin/datahub/releases/tag/v0.7.1)
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> - We're on [Slack](docs/slack.md) now! Ask questions and keep up with the latest announcements.
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## Introduction
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DataHub is LinkedIn's generalized metadata search & discovery tool. Read about the architectures of different metadata systems and why DataHub excels [here](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained). Also read our
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DataHub is LinkedIn's generalized metadata search & discovery tool. Read about the architectures of different metadata systems and why DataHub excels [here](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained). Also read our
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[LinkedIn Engineering blog post](https://engineering.linkedin.com/blog/2019/data-hub), check out our [Strata presentation](https://speakerdeck.com/shirshanka/the-evolution-of-metadata-linkedins-journey-strata-nyc-2019) and watch our [Crunch Conference Talk](https://www.youtube.com/watch?v=OB-O0Y6OYDE). You should also visit [DataHub Architecture](docs/architecture/architecture.md) to get a better understanding of how DataHub is implemented and [DataHub Onboarding Guide](docs/how/entity-onboarding.md) to understand how to extend DataHub for your own use cases.
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## Quickstart
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Please follow the [DataHub Quickstart Guide](https://datahubproject.io/docs/quickstart) to get a copy of DataHub up & running locally using [Docker](https://docker.com). As the guide assumes some basic knowledge of Docker, we'd recommend you to go through the "Hello World" example of [A Docker Tutorial for Beginners](https://docker-curriculum.com) if Docker is completely foreign to you.
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## Demo and Screenshots
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@ -82,80 +83,94 @@ There's a [hosted demo environment](https://datahubproject.io/docs/demo) where y
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[](https://datahubproject.io/docs/demo)
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## Source Code and Repositories
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* [linkedin/datahub](https://github.com/linkedin/datahub): This repository contains the complete source code for both DataHub's frontend & backend services. We currently follow a hybrid open source model for development in this repository. See [this blog post](https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p) for details on how we do it.
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* [linkedin/datahub-gma](https://github.com/linkedin/datahub-gma): This repository contains the source code for DataHub's metadata infrastructure libraries (Generalized Metadata Architecture, or GMA). We follow an open-source-first model for development in this repository.
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- [linkedin/datahub](https://github.com/linkedin/datahub): This repository contains the complete source code for both DataHub's frontend & backend services. We currently follow a hybrid open source model for development in this repository. See [this blog post](https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p) for details on how we do it.
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- [linkedin/datahub-gma](https://github.com/linkedin/datahub-gma): This repository contains the source code for DataHub's metadata infrastructure libraries (Generalized Metadata Architecture, or GMA). We follow an open-source-first model for development in this repository.
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## Documentation
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We have documentation available at [https://datahubproject.io/docs/](https://datahubproject.io/docs/).
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## Releases
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See [Releases](https://github.com/linkedin/datahub/releases) page for more details. We follow the [SemVer Specification](https://semver.org) when versioning the releases and adopt the [Keep a Changelog convention](https://keepachangelog.com/) for the changelog format.
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## FAQs
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Frequently Asked Questions about DataHub can be found [here](docs/faq.md).
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## Features & Roadmap
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Check out DataHub's [Features](docs/features.md) & [Roadmap](docs/roadmap.md).
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## Contributing
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We welcome contributions from the community. Please refer to our [Contributing Guidelines](docs/CONTRIBUTING.md) for more details. We also have a [contrib](contrib) directory for incubating experimental features.
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## Community
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Join our [slack workspace](https://slack.datahubproject.io) for discussions and important announcements. You can also find out more about our upcoming [town hall meetings](docs/townhalls.md) and view past recordings.
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## Adoption
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Here are the companies that have officially adopted DataHub. Please feel free to add yours to the list if we missed it.
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* [Expedia Group](http://expedia.com)
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* [Experius](https://www.experius.nl)
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* [Geotab](https://www.geotab.com)
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* [Grofers](https://grofers.com)
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* [Klarna](https://www.klarna.com)
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* [LinkedIn](http://linkedin.com)
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* [Saxo Bank](https://www.home.saxo)
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* [Shanghai HuaRui Bank](https://www.shrbank.com)
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* [ThoughtWorks](https://www.thoughtworks.com)
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* [TypeForm](http://typeform.com)
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* [Viasat](https://viasat.com)
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* [Wolt](https://wolt.com)
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Here are the companies that have officially adopted DataHub. Please feel free to add yours to the list if we missed it.
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- [Expedia Group](http://expedia.com)
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- [Experius](https://www.experius.nl)
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- [Geotab](https://www.geotab.com)
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- [Grofers](https://grofers.com)
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- [Klarna](https://www.klarna.com)
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- [LinkedIn](http://linkedin.com)
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- [Saxo Bank](https://www.home.saxo)
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- [Shanghai HuaRui Bank](https://www.shrbank.com)
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- [ThoughtWorks](https://www.thoughtworks.com)
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- [TypeForm](http://typeform.com)
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- [Viasat](https://viasat.com)
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- [Wolt](https://wolt.com)
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Here is a list of companies that are currently building POC or seriously evaluating DataHub.
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* [Amadeus](https://www.amadeus.com)
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* [Bizzy Group](https://www.bizzy.co.id)
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* [Booking.com](https://www.booking.com)
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* [City of New York, DoITT](https://www1.nyc.gov/site/doitt/index.page)
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* [Experian](https://www.experian.com)
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* [FlixBus](https://www.flixbus.com)
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* [Kindred Group](https://www.kindredgroup.com)
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* [Instructure](https://www.instructure.com)
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* [Inventec](https://www.inventec.com)
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* [Microsoft](https://microsoft.com)
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* [Morgan Stanley](https://www.morganstanley.com)
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* [Orange Telecom](https://www.orange.com)
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* [REEF Technology](https://reeftechnology.com)
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* [SpotHero](https://spothero.com)
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* [Sysco AS](https://sysco.no)
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* [University of Phoenix](https://www.phoenix.edu)
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* [Vectice](https://www.vectice.com)
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* [Weee!](https://www.sayweee.com)
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- [Amadeus](https://www.amadeus.com)
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- [Bizzy Group](https://www.bizzy.co.id)
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- [Booking.com](https://www.booking.com)
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- [City of New York, DoITT](https://www1.nyc.gov/site/doitt/index.page)
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- [Experian](https://www.experian.com)
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- [FlixBus](https://www.flixbus.com)
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- [Kindred Group](https://www.kindredgroup.com)
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- [Instructure](https://www.instructure.com)
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- [Inventec](https://www.inventec.com)
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- [Microsoft](https://microsoft.com)
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- [Morgan Stanley](https://www.morganstanley.com)
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- [Orange Telecom](https://www.orange.com)
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- [REEF Technology](https://reeftechnology.com)
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- [SpotHero](https://spothero.com)
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- [Sysco AS](https://sysco.no)
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- [University of Phoenix](https://www.phoenix.edu)
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- [Vectice](https://www.vectice.com)
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- [Weee!](https://www.sayweee.com)
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## Select Articles & Talks
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* [DataHub: A Generalized Metadata Search & Discovery Tool](https://engineering.linkedin.com/blog/2019/data-hub)
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* [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained)
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* [Open sourcing DataHub: LinkedIn’s metadata search and discovery platform](https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p)
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* [Driving DataOps Culture with LinkedIn DataHub](https://www.youtube.com/watch?v=ccsIKK9nVxk) @ [DataOps Unleashed 2021](https://dataopsunleashed.com/#shirshanka-session)
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* [DataHub: Powering LinkedIn's Metadata](docs/demo/DataHub_-_Powering_LinkedIn_Metadata.pdf) @ [Budapest Data Forum 2020](https://budapestdata.hu/2020/en/)
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* [Taming the Data Beast Using DataHub](https://www.youtube.com/watch?v=bo4OhiPro7Y) @ [Data Engineering Melbourne Meetup November 2020](https://www.meetup.com/Data-Engineering-Melbourne/events/kgnvlrybcpbjc/)
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* [Metadata Management And Integration At LinkedIn With DataHub](https://www.dataengineeringpodcast.com/datahub-metadata-management-episode-147/) @ [Data Engineering Podcast](https://www.dataengineeringpodcast.com)
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* [The evolution of metadata: LinkedIn’s story](https://speakerdeck.com/shirshanka/the-evolution-of-metadata-linkedins-journey-strata-nyc-2019) @ [Strata Data Conference 2019](https://conferences.oreilly.com/strata/strata-ny-2019.html)
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* [Journey of metadata at LinkedIn](https://www.youtube.com/watch?v=OB-O0Y6OYDE) @ [Crunch Data Conference 2019](https://crunchconf.com/2019)
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* [DataHub Journey with Expedia Group](https://www.youtube.com/watch?v=ajcRdB22s5o)
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* [Saxo Bank's Data Workbench](https://www.slideshare.net/SheetalPratik/linkedinsaxobankdataworkbench)
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* [Data Discoverability at SpotHero](https://www.slideshare.net/MaggieHays/data-discoverability-at-spothero)
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* [Data Catalogue — Knowing your data](https://medium.com/albert-franzi/data-catalogue-knowing-your-data-15f7d0724900)
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* [LinkedIn DataHub Application Architecture Quick Understanding](https://medium.com/@liangjunjiang/linkedin-datahub-application-architecture-quick-understanding-a5b7868ee205)
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* [A Dive Into Metadata Hubs](https://www.holistics.io/blog/a-dive-into-metadata-hubs/)
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* [25 Hot New Data Tools and What They DON’T Do](https://blog.amplifypartners.com/25-hot-new-data-tools-and-what-they-dont-do/)
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* [Emerging Architectures for Modern Data Infrastructure](https://a16z.com/2020/10/15/the-emerging-architectures-for-modern-data-infrastructure/)
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- [DataHub: A Generalized Metadata Search & Discovery Tool](https://engineering.linkedin.com/blog/2019/data-hub)
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- [DataHub: Popular Metadata Architectures Explained](https://engineering.linkedin.com/blog/2020/datahub-popular-metadata-architectures-explained)
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- [Open sourcing DataHub: LinkedIn’s metadata search and discovery platform](https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p)
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- [Driving DataOps Culture with LinkedIn DataHub](https://www.youtube.com/watch?v=ccsIKK9nVxk) @ [DataOps Unleashed 2021](https://dataopsunleashed.com/#shirshanka-session)
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- [DataHub: Powering LinkedIn's Metadata](docs/demo/DataHub_-_Powering_LinkedIn_Metadata.pdf) @ [Budapest Data Forum 2020](https://budapestdata.hu/2020/en/)
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- [Taming the Data Beast Using DataHub](https://www.youtube.com/watch?v=bo4OhiPro7Y) @ [Data Engineering Melbourne Meetup November 2020](https://www.meetup.com/Data-Engineering-Melbourne/events/kgnvlrybcpbjc/)
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- [Metadata Management And Integration At LinkedIn With DataHub](https://www.dataengineeringpodcast.com/datahub-metadata-management-episode-147/) @ [Data Engineering Podcast](https://www.dataengineeringpodcast.com)
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- [The evolution of metadata: LinkedIn’s story](https://speakerdeck.com/shirshanka/the-evolution-of-metadata-linkedins-journey-strata-nyc-2019) @ [Strata Data Conference 2019](https://conferences.oreilly.com/strata/strata-ny-2019.html)
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- [Journey of metadata at LinkedIn](https://www.youtube.com/watch?v=OB-O0Y6OYDE) @ [Crunch Data Conference 2019](https://crunchconf.com/2019)
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- [DataHub Journey with Expedia Group](https://www.youtube.com/watch?v=ajcRdB22s5o)
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- [Saxo Bank's Data Workbench](https://www.slideshare.net/SheetalPratik/linkedinsaxobankdataworkbench)
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- [Data Discoverability at SpotHero](https://www.slideshare.net/MaggieHays/data-discoverability-at-spothero)
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- [Data Catalogue — Knowing your data](https://medium.com/albert-franzi/data-catalogue-knowing-your-data-15f7d0724900)
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- [LinkedIn DataHub Application Architecture Quick Understanding](https://medium.com/@liangjunjiang/linkedin-datahub-application-architecture-quick-understanding-a5b7868ee205)
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- [A Dive Into Metadata Hubs](https://www.holistics.io/blog/a-dive-into-metadata-hubs/)
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- [25 Hot New Data Tools and What They DON’T Do](https://blog.amplifypartners.com/25-hot-new-data-tools-and-what-they-dont-do/)
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- [Emerging Architectures for Modern Data Infrastructure](https://a16z.com/2020/10/15/the-emerging-architectures-for-modern-data-infrastructure/)
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See the full list [here](docs/links.md).
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## License
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[Apache License 2.0](./LICENSE).
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