May 1, 2024
4 minute read
Kinesis Data Streams is an Amazon Web Services (AWS) service that enables you to collect, process, and analyze data from various sources, including applications, websites, IoT devices, and sensors. This powerful tool allows you to gain valuable insights from your data, enabling you to react to changes in the market, improve customer experiences, and drive innovation.
Why Learn Kinesis Data Streams?
There are several compelling reasons to learn Kinesis Data Streams:
u73ves|
Find a path to becoming a Kinesis Data Streams. Learn more at:
OpenCourser.com/topic/u73ves/kinesis
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Kinesis Data Streams.
Covers the fundamentals of stream processing using Apache Flink. It includes a chapter on how to use Flink with Kinesis Data Streams.
Covers the various data engineering services offered by AWS, including Kinesis Data Streams. It provides a good overview of the AWS ecosystem and how Kinesis Data Streams fits into it.
Covers the fundamentals of Apache Spark, a popular open-source data processing framework. It includes a chapter on how to use Spark with Kinesis Data Streams.
Covers the fundamentals of data-intensive text processing using MapReduce. It includes a chapter on how to use MapReduce with Kinesis Data Streams.
Covers the fundamentals of deep learning using TensorFlow. It includes a chapter on how to use TensorFlow with Kinesis Data Streams.
Covers the fundamentals of big data analytics using Python and Spark. It includes a chapter on how to use Python and Spark with Kinesis Data Streams.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/u73ves/kinesis