Data Stream Development via Spark, Kafka and Spring Boot

Rating 4.55 out of 5 (124 ratings in Udemy)

What you'll learn

Attain a solid foundation in the most powerful and versatile technologies involved in data streaming: Apache Spark and Apache Kafka
Form a robust and clean architecture for a data streaming pipeline
Implement the correct tools to bring your data streaming architecture to life
Isolate the most problematic tradeoff for each tier involved in a data streaming pipeline
Query, analyze, and apply machine learning algorithms to …

Rating 4.55 out of 5 (124 ratings in Udemy)

What you'll learn

Attain a solid foundation in the most powerful and versatile technologies involved in data streaming: Apache Spark and Apache Kafka
Form a robust and clean architecture for a data streaming pipeline
Implement the correct tools to bring your data streaming architecture to life
Isolate the most problematic tradeoff for each tier involved in a data streaming pipeline
Query, analyze, and apply machine learning algorithms to collected data
Display analyzed pipeline data via Google Maps on your web browser
Discover and resolve difficulties in scaling and securing data streaming applications

Description

Today, organizations have a difficult time working with huge numbers of datasets. In addition, data processing and analyzing need to be done in real time to gain insights. This is where data streaming comes in. As big data is no longer a niche topic, having the skillset to architect and develop robust data streaming pipelines is a must for all developers. In addition, they also need to think of the entire pipeline, including the trade-offs for every tier.

This course starts by explaining the blueprint architecture for developing a completely functional data streaming pipeline and installing the technologies used. With the help of live coding sessions, you will get hands-on with architecting every tier of the pipeline. You will also handle specific issues encountered working with streaming data. You will input a live data stream of Meetup RSVPs that will be analyzed and displayed via Google Maps.

By the end of the course, you will have built an efficient data streaming pipeline and will be able to analyze its various tiers, ensuring a continuous flow of data.

About the Author

Anghel Leonard is currently a Java chief architect. He is a member of the Java EE Guardians with 20+ years’ experience. He has spent most of his career architecting distributed systems. He is also the author of several books, a speaker, and a big fan of working with data.

Duration 7 Hours 58 Minutes

Paid

Self paced

Beginner Level

English (US)

989

Rating 4.55 out of 5 (124 ratings in Udemy)

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