Streaming ETL – The
New Data Integration

Streaming ETL – The</br>New Data Integration

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Overview

What if there is a way for you to create views of data and have them update automatically, enhance operational efforts and reduce work? With Confluent’s event-driven streaming platform, you can deliver your data slices off of always up-to-date sources, whether they’re coming from hundreds or billions of daily events.

In this online talk series, we’ll show you the modern way of integrating data through streaming extract, transform and load (ETL). Join us for three different sessions on how modern streaming ETL delivers event-driven data to businesses, and find out how you can make seamless data integration a reality in your organization.


Part 01:
The Future of ETL 
Isn't What It Used to Be

May 23, 2018, at 9:00 am PT | 12:00 pm ET

Join Gwen Shapira, Apache Kafka® committer and co-author of "Kafka: The Definitive Guide," as she presents core patterns of modern data engineering and explains how you can use microservices, event streams and a streaming platform like Apache Kafka to build scalable and reliable data pipelines designed to evolve over time. 

Gwen Shapira

Gwen Shapira

Principal Data Architect, Confluent


Part 02:
Steps to Building a Streaming ETL Pipeline with Apache Kafka® and KSQL

June 6, 2018, at 9:00 am PT | 12:00 pm ET

In this talk, we'll build a streaming data pipeline using nothing but our bare hands, the Kafka Connect API and KSQL. We'll stream data in from MySQL, transform it with KSQL and stream it out to Elasticsearch. Options for integrating databases with Kafka using CDC and Kafka Connect will be covered as well.

Robin Moffatt

Robin Moffatt

Developer Advocate, Confluent


Part 03:
Streaming Transformations -
Putting the T in Streaming ETL

June 20, 2018, at 9:00 am PT | 12:00 pm ET

We’ll discuss how to leverage some of the more advanced transformation capabilities available in both KSQL and Kafka Connect, including how to chain them together into powerful combinations for handling tasks such as data-masking, restructuring and aggregations. Using KSQL, you can deliver the streaming transformation capability easily and quickly.

Nick Dearden

Nick Dearden

Director of Engineering, Confluent

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