Modern Data Processing _ Big Data Analytical Streaming Data Pipelines https://github.com/tspannhw/FLiP-Pi-DeltaLake-Thermal/blob/main/README.md https://www.meetup.com/sf-big-analytics/events/286983210/ Details Please register on the event website to receive your customized zoom joining link: 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