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Study mode:
on
1
Intro
2
Data volumes
3
Shortterm vs longterm
4
Why Avro
5
Why Parquet
6
Flink
7
UI
8
API
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AWS Data Lake
Description:
Explore the intricacies of IoT data management on AWS in this 20-minute conference talk. Dive into two primary use cases for captured metric data: real-time analysis and ad-hoc analysis. Learn about robust streaming frameworks, with a focus on Apache Flink and a brief discussion of Apache Beam. Examine best practices for data persistence, comparing various serialization formats and their suitability for different analysis scenarios. Gain insights into fully managed solutions like AWS Data Lake, weighing their pros and cons. Cover topics such as data volumes, short-term vs. long-term storage, Avro and Parquet formats, Flink UI and API, and AWS Data Lake implementation.

IoT Data Processing and Analysis on AWS - Real-Time and Ad-Hoc Approaches

ChariotSolutions
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