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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
Save this course
Save Building ETL Pipelines from Streaming Data with Kafka and ksqlDB to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Building ETL Pipelines from Streaming Data with Kafka and ksqlDB with these
activities:
Course Notes Organization
Show steps
Improve your learning experience by organizing and reviewing your course notes.
Show steps
-
Create a system for organizing your notes
-
Regularly review and update your notes
Create a Kafka cluster and produce data
Show steps
Reinforce your understanding of Kafka's core functionality by setting up a cluster and working with data.
Show steps
-
Install Kafka and create a cluster with ZooKeeper.
-
Use a command-line tool to produce data to a Kafka topic.
-
Monitor the Kafka cluster using metrics and dashboards.
Read Kafka: The Definitive Guide
Show steps
Build a strong foundation in Kafka's architecture and key concepts by reviewing this reference book.
View
Kafka: The Definitive Guide: Real-Time Data and...
on Amazon
Show steps
-
Review the chapters on Kafka architecture and data model.
-
Understand the basics of Kafka Streams and ksqlDB for stream processing.
-
Explore use cases and best practices for working with Kafka in real-time data pipelines.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Study Group Discussions
Show steps
Join a study group to discuss the course material and collaborate on projects.
Show steps
-
Find or create a study group
-
Regularly meet with your group to discuss the material
Complete the official Kafka Streams tutorial
Show steps
Deepen your understanding of stream processing concepts by following the official Kafka Streams tutorial.
Show steps
-
Set up your development environment and create a Kafka Streams application.
-
Implement a simple data transformation pipeline using Kafka Streams.
-
Deploy and test your Kafka Streams application.
Write a blog post or article on Kafka stream processing
Show steps
Consolidate your learning by creating a blog post or article that shares your insights on Kafka stream processing.
Browse courses on
Technical Writing
Show steps
-
Choose a specific topic related to Kafka stream processing.
-
Research and gather information on the topic.
-
Write a well-structured and informative blog post or article.
-
Publish your blog post or article on a relevant platform.
Kafka Streams Tutorial
Show steps
Solidify your understanding of Kafka Streams by following along with an official tutorial.
Show steps
-
Explore the official Apache Kafka Streams tutorial
-
Implement the code examples in your own environment
Data Visualization
Show steps
Create a data visualization tool that aggregates and analyzes data from Kafka streams.
Browse courses on
Data Visualization
Show steps
-
Choose a data visualization library
-
Design the visualization
-
Implement the data visualization
Participate in a Kafka hackathon
Show steps
Challenge yourself and showcase your skills by participating in a Kafka hackathon.
Browse courses on
Innovation
Show steps
-
Find a Kafka hackathon and register your team.
-
Develop a creative solution that leverages Kafka's capabilities.
-
Present your solução at the hackathon and compete for prizes.
Mentor junior engineers on Kafka
Show steps
Share your knowledge and expertise by mentoring others in the field.
Browse courses on
Mentoring
Show steps
-
Identify junior engineers who are interested in learning about Kafka.
-
Provide guidance and support on Kafka concepts and best practices.
-
Review their work and provide feedback.
Course Notes Organization
Show steps
Improve your learning experience by organizing and reviewing your course notes.
Show steps
Show steps
Show steps
- Create a system for organizing your notes
- Regularly review and update your notes
Create a Kafka cluster and produce data
Show steps
Reinforce your understanding of Kafka's core functionality by setting up a cluster and working with data.
Show steps
Show steps
Show steps
- Install Kafka and create a cluster with ZooKeeper.
- Use a command-line tool to produce data to a Kafka topic.
- Monitor the Kafka cluster using metrics and dashboards.
Read Kafka: The Definitive Guide
Show steps
Build a strong foundation in Kafka's architecture and key concepts by reviewing this reference book.
View
Kafka: The Definitive Guide: Real-Time Data and...
on Amazon
Show steps
Show steps
Show steps
- Review the chapters on Kafka architecture and data model.
- Understand the basics of Kafka Streams and ksqlDB for stream processing.
- Explore use cases and best practices for working with Kafka in real-time data pipelines.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Study Group Discussions
Show steps
Join a study group to discuss the course material and collaborate on projects.
Show steps
Show steps
Show steps
- Find or create a study group
- Regularly meet with your group to discuss the material
Complete the official Kafka Streams tutorial
Show steps
Deepen your understanding of stream processing concepts by following the official Kafka Streams tutorial.
Show steps
Show steps
Show steps
- Set up your development environment and create a Kafka Streams application.
- Implement a simple data transformation pipeline using Kafka Streams.
- Deploy and test your Kafka Streams application.
Write a blog post or article on Kafka stream processing
Show steps
Consolidate your learning by creating a blog post or article that shares your insights on Kafka stream processing.
Browse courses on
Technical Writing
Show steps
Show steps
Show steps
- Choose a specific topic related to Kafka stream processing.
- Research and gather information on the topic.
- Write a well-structured and informative blog post or article.
- Publish your blog post or article on a relevant platform.
Kafka Streams Tutorial
Show steps
Solidify your understanding of Kafka Streams by following along with an official tutorial.
Show steps
Show steps
Show steps
- Explore the official Apache Kafka Streams tutorial
- Implement the code examples in your own environment
Data Visualization
Show steps
Create a data visualization tool that aggregates and analyzes data from Kafka streams.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a data visualization library
- Design the visualization
- Implement the data visualization
Participate in a Kafka hackathon
Show steps
Challenge yourself and showcase your skills by participating in a Kafka hackathon.
Browse courses on
Innovation
Show steps
Show steps
Show steps
- Find a Kafka hackathon and register your team.
- Develop a creative solution that leverages Kafka's capabilities.
- Present your solução at the hackathon and compete for prizes.
Mentor junior engineers on Kafka
Show steps
Share your knowledge and expertise by mentoring others in the field.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify junior engineers who are interested in learning about Kafka.
- Provide guidance and support on Kafka concepts and best practices.
- Review their work and provide feedback.
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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