Managing data pipelines and data drift for Machine Learning

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

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Follow StreamSets:  https://twitter.com/streamsets
Follow Girish Pancha:  https://twitter.com/girishpancha
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