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Building ETL Pipelines from Streaming Data with Kafka and ksqlDB
Eugene Meidinger
Eugene Meidinger
Kafka can do more than just storing streaming data. This course will teach you to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams.
Read more
Kafka can do more than just storing streaming data. This course will teach you to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams.
Read more
Kafka can do more than just storing streaming data. This course will teach you to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams.
There is plenty of value in learning how to turn Kafka into a stream analytics engine. In this course, Building ETL Pipelines from Streaming Data with Kafka and KSQL, you’ll learn to shape and transform your Kafka streaming data. First, you’ll explore how ksqlDB and Kafka Streams both solve this problem. Next, you’ll discover how to transform your streams. Finally, you’ll learn how to aggregate and enrich data. When you’re finished with this course, you’ll have the skills and knowledge of ksqlDB and Kafka Streams needed to extract insights from Kafka streaming data.
Register for this course and see more details by visiting:
OpenCourser.com/course/si1p0t/building
What's inside
Syllabus
Course Overview
What Are ksqlDB and Kafka Streams?
Configuring ksqlDB and CLI
Deploying ksqlDB Queries
Read more
Syllabus
Course Overview
What Are ksqlDB and Kafka Streams?
Configuring ksqlDB and CLI
Deploying ksqlDB Queries
Read more
Understanding Advanced Stream Processing
Creating a Kafka Streams Application
Aggregating and Enriching Data with Kafka Streams
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on ksqlDB and Kafka Streams, making it a good fit for learners interested in deep expertise in these topics
Taught by Eugene Meidinger, an expert on the subject matter
Provides hands-on practice with ksqlDB and Kafka Streams
Builds a foundation for learners new to stream analytics
Develops expertise for experienced learners looking to enhance their knowledge of stream analytics
Covers advanced stream processing, suitable for learners with existing knowledge of stream analytics
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Activities
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Building ETL Pipelines from Streaming Data with Kafka and ksqlDB.
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Career center
Learners who complete Building ETL Pipelines from Streaming Data with Kafka and ksqlDB will develop knowledge and skills
that may be useful to these careers:
Data Architect
Data Architect
Data Architects design, build, and maintain data management systems. They ensure that data is accessible, reliable, and secure. This course can help you build a foundation for a career as a Data Architect by teaching you how to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams. You'll also learn how to transform your streams and enrich data.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. They work with data from a variety of sources to create data sets that can be used for analysis and decision-making. This course can help you build a foundation for a career as a Data Engineer by teaching you how to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams. You'll also learn how to transform your streams and enrich data.
Data Scientist
Data Scientist
Data Scientists use data to solve problems and make decisions. They work with data from a variety of sources to create models that can be used to predict future outcomes. This course can help you build a foundation for a career as a Data Scientist by teaching you how to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams. You'll also learn how to transform your streams and enrich data.
Database Administrator
Database Administrator
Database Administrators design, build, and maintain databases. They ensure that databases are accessible, reliable, and secure. This course can help you build a foundation for a career as a Database Administrator by teaching you how to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams. You'll also learn how to transform your streams and enrich data.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software systems. They work with a variety of programming languages and technologies to create software that meets the needs of users. This course can help you build a foundation for a career as a Software Engineer by teaching you how to aggregate and analyze data in Kafka with ksqlDB and Kafka Streams. You'll also learn how to transform your streams and enrich data.
For more career information including salaries, visit:
OpenCourser.com/course/si1p0t/building
Reading list
We've selected eight 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
Building ETL Pipelines from Streaming Data with Kafka and ksqlDB.
Provides a comprehensive overview of Apache Kafka, covering its architecture, key concepts, and use cases. It valuable reference for understanding the fundamentals of Kafka and how it can be used to build scalable and reliable data pipelines.
Provides a comprehensive overview of Apache Flink, with a focus on how to use it to build scalable and reliable streaming data pipelines. It would be a valuable resource for anyone who wants to learn more about Apache Flink or use it in their own projects.
Provides a comprehensive overview of statistical learning with R. It covers everything from the basics of statistical learning to advanced topics such as supervised learning and unsupervised learning.
Provides a comprehensive overview of data science from scratch. It covers everything from the basics of data science to advanced topics such as machine learning and deep learning.
Provides a comprehensive overview of applied predictive analytics. It covers everything from the basics of predictive analytics to advanced topics such as model selection and evaluation.
Provides a comprehensive overview of data-intensive text processing with MapReduce. It covers everything from the basics of MapReduce to advanced topics such as natural language processing and machine learning.
Provides a comprehensive overview of machine learning with R. It covers everything from the basics of R to advanced topics such as supervised learning and unsupervised learning.
Provides a gentle introduction to Apache Kafka. It covers topics such as Kafka's architecture, key concepts, and use cases. It good starting point for developers who want to learn the basics of Kafka.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/si1p0t/building
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Time
155 hours
Level
Intermediate
Via
Pluralsight
Instructor
Eugene Meidinger
Language
English
Good to know
Focuses on ksqlDB and Kafka Streams, making it a good fit for learners interested in deep expertise in these topics
Taught by Eugene Meidinger, an expert on the subject matter
Provides hands-on practice with ksqlDB and Kafka Streams
Builds a foundation for learners new to stream analytics
Develops expertise for experienced learners looking to enhance their knowledge of stream analytics
Covers advanced stream processing, suitable for learners with existing knowledge of stream analytics
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