Managing data pipelines and data drifts for Machine Learning

From the creator

Watch this episode with Ruth Yakubu @ruthieyakubu and Girish Pancha @girishpancha on how StreamSets provides a multi-cloud DataOps platform designed to offer modern data integration, helping enterprises to continuously flow big, streaming and traditional data handles data drift, ETL processing and ML with a cloud-native operations portal for the continuous automation and monitoring of complex multi-pipeline topologies.​ An exceptional conversation with Girish Pancha, CEO of StreamSets who have raise over $77M in funding for their data platform empowers companies' modern analytics and digital transformation with continuous data that enables data scientists and data engineers to design, deploy and operate smart data pipelines for rapidly changing data. In this session, we will discuss how the company accelerates the process of data ingest, analytics and data drifts. 👩‍💻 Hands-on learning Resources: Azure Data drifts: https://aka.ms/TEDataDrifts Azure Spark, Kafka: https://aka.ms/TESparkKafka Azure Synapse Pipelines: https://aka.ms/TESynapse Azure Databricks: https://aka.ms/TEDatabricks 📌Let's connect: Follow Ruth Yakubu: https://twitter.com/ruthieyakubu Follow Tech Exceptions: https://twitter.com/TechExceptions Follow StreamSets: https://twitter.com/streamsets Follow Girish Pancha: https://twitter.com/girishpancha 🔔Subscribe to our channel for more AI and Data episodes and playlist: https://aka.ms/TECh9 💡 Checkout our other channels for move on AI/ML tips & tri

Published 2021-04-21 · Watch on YouTube ↗
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