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Streaming Data Pipelines

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May 11, 2024 3 minute read
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Streaming Data Pipelines refers to the process of continuously ingesting, processing, and analyzing data streams in real-time or near real-time. Streaming data is a continuous flow of data that is generated constantly and typically arrives in small chunks over time. Streaming data pipelines are designed to handle this deluge of data efficiently and provide insights in a timely manner.

Benefits and Applications

Streaming data pipelines hold immense value in various industries and applications, including:

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Reading list

We've selected three 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 Streaming Data Pipelines.
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Streaming Systems
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Provides a deep dive into the design and implementation of streaming systems. It covers topics such as stream processing algorithms, fault tolerance, and scaling.
Streaming Systems: The What, Where, When, and How...
Paperback
$$$
Streaming Systems: The What, Where, When, and How...
Kindle Edition
$$
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Designing Data-Intensive Applications
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Provides a broad overview of designing and building data-intensive applications. It covers topics such as data modeling, data storage, and data processing, including streaming data pipelines.
Designing Data-Intensive Applications: The Big...
Paperback
$$
Designing Data-Intensive Applications: The Big...
Kindle Edition
$$
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Data Pipelines Pocket Reference
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Provides a quick and easy reference guide to topics related to data pipelines, including streaming data pipelines. It covers topics such as data pipeline components, data formats, and monitoring.
Data Pipelines Pocket Reference: Moving and...
Paperback
$$
Data Pipelines Pocket Reference: Moving and...
Kindle Edition
$$
Relevant careers
Data Engineer
Data Analyst
Data Scientist
Software Engineer
Cloud Architect
Database Administrator
Information Security Analyst
Project Manager
Operations Analyst
Business Intelligence Analyst
Related topics
Data Pipelines
Stream Processing
Big Data Analytics
Event-Driven Architecture
Time Series Analysis
Parallel Computing
Data Warehousing
NOSQL Databases
Data Mining
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