Name: Modern Data Processing With Streaming Data Pipelines
Start: 2022-07-26T12:00:00-07:00
End: 2022-07-26T13:00:00-07:00

Please register on the event website to receive your customized zoom joining link: [https://www.aicamp.ai/event/eventdetails/W2022072612](https://www.aicamp.ai/event/eventdetails/W2022072612)
(Our partner AICamp provides free Zoom service for our members)

**Agenda:**
12:00 - 12:05 pm members join online

12:05 - 1 pm talk + QA

1 pm – closing

**Summary:** In our meetup talk, we will show some best practices we have discovered over the last 7 years in building data streaming applications including IoT, CDC, Logs, and data feed.

In our modern data processing approach, we utilize several highly scalable open-source frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Pulsar.

From there we build streaming ETL with Apache Spark, and enhance events with Pulsar Functions for ML and enrichment.

We build continuous queries against our topics with Flink SQL for aggregations, real-time alerts, and Delta Lake population.

With Slides, Demos, Q&A

**Speakers: Timothy Spann and David** **Kjerrumgaard**

Timothy Spann

Developer Advocate, StreamNative
Former Principal DataFlow Field Engineer at Cloudera
Former Senior Solutions Engineer at Hortonworks
Former Senior Field Engineer at Pivotal
DZone MVB Blogger

David Kjerrumgaard

Developer Advocate
Apache Pulsar Committer \| Author of Pulsar In Action
Former Principal Software Engineer on Splunk’s messaging team Responsible for Splunk’s internal Pulsar-as-a-Service platform
Former Director of Solution Architecture at Streamlio

AnyaB

SF Big Analytics

Technology

Hadoop

Big Data

Machine Learning

Text Analytics

Data Analytics

Data Visualization

Predictive Analytics

Data Mining

Business Analytics

Data Science

Advanced Analytics

Cloud Analytics

Apache Spark

Modern Data Processing With Streaming Data Pipelines

Spark Streaming

Apache Flink

Apache Nifi

Apache Pulsar

Online event

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Modern Data Processing With Streaming Data Pipelines

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