finelybook
Designing Cloud Data Platforms
by 作者: Danil Zburivsky and Lynda Partner
Publisher Finelybook 出版社: Manning Publications; 1st edition (1 Jan. 2000)
Language 语言: English
pages 页数: 336 pages
ISBN-10 书号: 1617296449
ISBN-13 书号: 9781617296444
Book Description
Centralized data warehouses,the long-time defacto standard for housing data for analytics,are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is a hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read,you’ll learn the core components of a cloud data platform design,along with the role of key technologies like Spark and Kafka Streams. You’ll also explore setting up processes to manage cloud-based data,keep it secure,and using advanced analytic and BI tools to analyze it.
Well-designed pipelines,storage systems,and APIs eliminate the complicated scaling and maintenance required with on-prem data centers. Once you learn the patterns for designing cloud data platforms,you’ll maximize performance no matter which cloud vendor you use.
In Designing Cloud Data Platforms,Danil Zburivsky and Lynda Partner reveal a six-layer approach that increases flexibility and reduces costs. Discover patterns for ingesting data from a variety of sources,then learn to harness pre-built services provided by 作者: cloud vendors.
What’s inside
Best practices for structured and unstructured data sets
Cloud-ready machine learning tools
Metadata and real-time analytics
Defensive architecture,access,and security
