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Robust data pipelines with smart contracts Webinar

20-11-2020WATCH ON YOUTUBE ↗

📖Get started with Daml: https://bit.ly/tryDaml 📚Learn more about Daml Smart Contracts: https://bit.ly/learn_daml 📮Check out our blogs: https://bit.ly/daml-blog-engineering 📋Become a Daml certified expert: https://bit.ly/daml-certification

SMART CONTRACTS FRANKFURT & FRANKFURT DATA SCIENCE An online meetup by Smart Contracts Frankfurt and Frankfurt Data Science communities. Data Scientists already acknowledge the significant performance gains from automated data pipelines. However, legitimate concerns still remain. In order to meet principles and standards for quality research many data scientists responsibly expect proofs of reliability in handling the data as well as execution of each step of the process. In this meetup with the support by our content partner and technology leader DAML we would like to demonstrate how smart contracts will improve data engineering by developing verifiable robust data pipelines. www.meetup.com/Frankfurt-Smart-Contracts-Meetup www.daml.com

ABOUT Any data scientist will tell you how data collection and preparation dominate their activity. This becomes an understatement the moment you put your model into a productive system. Building data pipelines that preserve data consistency, accessibility and also enforce privacy requirements is a task for a larger team.

Can smart contracts help? We think so and would like to debunk the myth that smart contracts are only about blockchain and finance. Together we'll look into a larger data pipeline from an AI / automotive use case and see how DAML and a cool startup in NYC could fit into the toolset of a modern data team.

PROGRAMME Introduction: Ali Pasha, Miguel Vaz // Smart Contracts Frankfurt Eldar Rakhmatullaev // Frankfurt Data Science Francesco Andreoli, Manish Grover // DAML www.linkedin.com/in/alipashaforoughi www.linkedin.com/in/miguelvaz www.linkedin.com/in/francescoandreoli www.linkedin.com/in/manishgrover

Talk: Large scale data pipelines for autonomous driving by Dr. Michael Lin