Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
By 作者: James Densmore
pages 页数: 200 pages
Edition 版本: 1
Language 语言: English
Publisher Finelybook 出版社: O'Reilly Media
Publication Date 出版日期: 2021-06-15
The Book Description robot was collected from Amazon and arranged by Finelybook
Data pipelines are the foundation for success in data analytics and machine learning. Moving data from many diverse sources and processing it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack.
You'll learn common considerations and key decision points when implementing pipelines, such as data pipeline design patterns, data ingestion implementation, data transformation, the orchestration of pipelines, and build versus buy decision making. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions.
What a data pipeline is and how it works
How data is moved and processed on modern data infrastructure, including cloud platforms
Common tools and products used by data engineers to build pipelines
How pipelines support machine learning and analytics needs
Considerations for pipeline maintenance, testing, and alerting