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cloud-data-engineering-for-dummies PDF 下载
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collect, store, and analyze their data in one place, so they can easily obtain all types of insights from their data. And they want to
simplify and democratize the exploration of that data, automate
routine data management activities, and support a broad range of
data and analytics workloads.
A properly architected cloud data platform brings this all together
with a highly integrated set of services that streamline how data
is used. It enables you to consolidate diverse analytic activities,
orchestrate the secure sharing and exchange of data, and populate
modern business applications with data (see Figure 5-1).
FIGURE 5-1: The fundamental elements of a modern cloud data platform.
By creating a single place for all types of data and all types of
data workloads, a cloud data platform can dramatically simplify
your infrastructure, without incurring the costs inherent in traditional architectures. For example, by centralizing data, you reduce
the number of stages the data needs to move through before it
becomes actionable, which eliminates the need for complex data
pipeline tools. By reducing the wait time for data, you allow users
to obtain the insights they need, when they need them, so they
can immediately spot business opportunities and address pressing issues. One unified platform can handle everything you used
to do in a data warehouse, data lake, and multiple data marts.
Modern cloud data platforms include critical capabilities to set
the foundation for reliable and efficient data pipelines for moving
all your data to the cloud. From there, the data undergoes various
transformations until it is usable for analytics, data science, data
sharing, and other business initiatives.
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