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#537: [Right Now at AWS] Improve Content & Reduce Churn with External Datasets

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Manage episode 334938160 series 1527787
Content provided by Amazon Web Services. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Amazon Web Services or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Media and entertainment (M&E) companies are improving content, reducing churn, and solving persistent challenges, like title matching, with third-party, external data sources. Yet, incorporating external data can be challenging with various vendors and integration methods. In this episode, Harry Lin, AWS Data Exchange Business Development Specialist for M&E, shares emerging data use cases and strategies to simplify data integration into workflows. Learn more - https://www.linkedin.com/smart-links/AQFMzIRNUfyGUg Leave us feedback - https://d1ox81nm0qxip8.cloudfront.net/index.html
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666 episodes

Artwork
iconShare
 
Manage episode 334938160 series 1527787
Content provided by Amazon Web Services. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Amazon Web Services or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Media and entertainment (M&E) companies are improving content, reducing churn, and solving persistent challenges, like title matching, with third-party, external data sources. Yet, incorporating external data can be challenging with various vendors and integration methods. In this episode, Harry Lin, AWS Data Exchange Business Development Specialist for M&E, shares emerging data use cases and strategies to simplify data integration into workflows. Learn more - https://www.linkedin.com/smart-links/AQFMzIRNUfyGUg Leave us feedback - https://d1ox81nm0qxip8.cloudfront.net/index.html
  continue reading

666 episodes

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