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Designing cloud data platforms, danil zburivsky, lynda partner

850 грн

Описание

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.

about the technology

\nWell-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. \n \n

about the book

\nIn 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 cloud vendors. \n \n

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