[In-person] Data Stream Processing Night - Silicon Valley

Please register on the event website: https://www.aicamp.ai/event/eventdetails/W2022110218

(Food/drink will be provided, Swags/Prizes, free parking)

Data streaming platforms provide the tools needed to bring together real-time streams of data. It enables data intelligent, real-time applications and systems, and empowers teams to act on data instantly.

We will host a series of meetup events to showcase some of the cutting edge developments that are happening in data stream processing in the open sourced tools and industry. We will invite the PMCs of Apache Beam, Airflow, Spark, Flink, Kafka, etc.. and teams who use these tools to share practical experiences, best practices in building data stream processing pipelines. The community of real-time technology leaders and developers will come together to share best practices and use cases as well as explore the vision and future of data streaming.

Agenda:
* 6:00pm~6:30pm: Checkin and Food/drink
* 6:30pm~8:00pm: Tech talks
* 8:00pm~8:30pm: Networking and closing

Tech Talk 1: Apache Beam - fully language portable and scalable batch and streaming data processing.
Abstract: Apache Beam introduces a unified programming model for batch and streaming data processing. Beam provides SDKs for various programming languages, for example, Java, Python and Go and Beam pipelines are executed in a runner, for example, Apache Flink, Apache Spark and Google Cloud Dataflow. Beam provides a portability framework that allows a given runner to execute transforms defined in any given SDK. This lets Beam runners maintain one implementation that supports all current and future SDKs. Additionally, this allows Beam runners to use transforms from different SDK languages in the same pipeline. In this talk, we'll look into Apache Beam’s portability framework and its benefits.
Speaker: Chamikara Jayalath, Google

Tech Talk 2: TBD

Partners:
Z-park Silicon Valley Innovation Center