Streaming Concepts
Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.
Start Course for Free2 hours16 videos47 exercises3,704 learnersStatement of Accomplishment
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Training 2 or more people?
Try DataCamp for BusinessLoved by learners at thousands of companies
Course Description
Streaming is a huge aspect of the data world right now and is being used by nearly every industry from manufacturing to healthcare. Would you like to learn more about the general concepts behind data pipelines and how the processes work?
This course provides a general introduction to streaming concepts including batching, queuing, and stream processing along with where they fit into data processing frameworks. It covers real-world examples of how streaming is implemented in production. It is designed as a general introduction to these concepts and does not require an extensive background in data processing.
This course provides a general introduction to streaming concepts including batching, queuing, and stream processing along with where they fit into data processing frameworks. It covers real-world examples of how streaming is implemented in production. It is designed as a general introduction to these concepts and does not require an extensive background in data processing.
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.In the following Tracks
Professional Data Engineer in Python
Go To Track- 1
Methods for Processing Data
FreeIn this chapter, you’ll be given an introduction to basic concepts in batch data processing, revolving around implementation, scaling, and potential challenges during use.
- 2
Intro to Streaming
Here, you’ll learn about the basics of streaming, event-based data processing, and the advantages over traditional batch-based data processing.
Intro to event-based computing50 xpIn the event of...100 xpWelcome to the event!100 xpQueuing50 xpQueue characteristics100 xpTo queue or not to queue100 xpSingle system data streaming50 xpLog stream order100 xpLog options100 xpBatching vs. streaming50 xpBatch, queue, or stream?100 xpLog stream processor100 xp - 3
Streaming Systems
This chapter introduces the concepts behind modern streaming systems, how to scale them, and some of the issues found in using streaming processes.
Intro to real-time streaming50 xpReal-time?100 xpIs it real this time?100 xpVertically scaling streaming systems50 xpScaling reasons50 xpTo vertically scale...?100 xpHorizontally scaling streaming systems50 xpUpscaled out100 xpSLA guarantees100 xpStreaming roadblocks50 xpStreaming attributes100 xpIssue types100 xpStreaming challenges100 xp - 4
Real-World Use Cases
In this final chapter, you’ll learn about common streaming systems and consider the implementation of streaming data processing in different use cases.
Popular streaming systems50 xpStreaming truths100 xpCrossing the streams...100 xpReal-world use case: streaming music service50 xpMessage components100 xpAnswer me this...100 xpReal-world use case: sensor data50 xpGreat order of the SLAs100 xpSensor scaling considerations100 xpReal-world use case: vaccination clinic50 xpVaccination clinic - classify areas100 xpA new problem...100 xpCongratulations!50 xp
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.In the following Tracks
Professional Data Engineer in Python
Go To Trackcollaborators
prerequisites
Understanding Data Engineering
Mike MetzgerData Engineer Consultant @ Flexible Creations
Mike is a consultant focusing on data engineering and analysis using SQL, Python, and Apache Spark among other technologies. He has a 20+ year history of working with various technologies in the data, networking, and security space.
What do other learners have to say?
Join over 15 million learners and start Streaming Concepts today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.