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Analyzing Data Streams in Real Time with Amazon Kinesis: PNNL's Serverless Data Lake Ingestion
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*As of August 30th, 2023, Kinesis Data Analytics is now Amazon Managed Service for Apache Flink*
AWS Public Sector Summit 2018 - Washington, D.C.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. In this session, we first present an end-to-end streaming data solution using Amazon Kinesis Data Streams for data ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose for persistence. We review in detail how to write SQL queries for operational monitoring using Kinesis Data Analytics.
Learn how PNNL is building their ingestion flow into their Serverless Data Lake leveraging the Kinesis Platform. At times migrating existing NiFi Processes where applicable to various parts of the Kinesis Platform, replacing complex flows on Nifi to bundle and compress the data with Kinesis Firehose, leveraging Kinesis Streams for their enrichment and transformation pipelines, and using Kinesis Analytics to Filter, Aggregate, and detect anomalies.
Speakers: Mike Giardinelli, Ralph Perko, Randy Ridgley
AWS Public Sector Summit 2018 - Washington, D.C.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. In this session, we first present an end-to-end streaming data solution using Amazon Kinesis Data Streams for data ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon Kinesis Data Firehose for persistence. We review in detail how to write SQL queries for operational monitoring using Kinesis Data Analytics.
Learn how PNNL is building their ingestion flow into their Serverless Data Lake leveraging the Kinesis Platform. At times migrating existing NiFi Processes where applicable to various parts of the Kinesis Platform, replacing complex flows on Nifi to bundle and compress the data with Kinesis Firehose, leveraging Kinesis Streams for their enrichment and transformation pipelines, and using Kinesis Analytics to Filter, Aggregate, and detect anomalies.
Speakers: Mike Giardinelli, Ralph Perko, Randy Ridgley
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