Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 51 Minute(s)
Language
English
Taught by
Packt Publishing
Rating
1 views
Course Overview
Handle high volumes of data at high speed. Architect and implement an end-to-end data streaming pipeline
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.
Course Content
- 5 section(s)
- 27 lecture(s)
- Section 1 Introducing Data Streaming Architecture
- Section 2 Deployment of Collection and Message Queuing Tiers
- Section 3 Proceeding to the Data Access Tier
- Section 4 Implementing the Analysis Tier
- Section 5 Mitigate Data Loss between Collection, Analysis and Message Queuing Tiers
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
Reviews
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SSrinivas Reddy
not good content and example streaming wc website do not work.. just reading from a book...
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SStathis Andronikos
Great in explaining concepts and basic architecture.
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BBhanu
Author speaks very slow. I had to use 1.25x playback. Moreover there are not enough examples to support what author is trying to say. I had to google always for everything. Author is just reading the slides and sometimes it looks like I am seeing a powerpoint presentation. On the positive side, the structure of this course is excellent. I mean every piece is introduced at the right time and place.
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MMartin McAlroy
Very useful and informative for an introduction into this topic. Perhaps more practical examples along with the conceptual information would also help e.g. specific code snippets shown alongside the concept and used as a way to explain what is going on by comparing the more abstract ideas with the more low-level, intricate code in use.
