Exam Ref DP-900 Microsoft Azure Data Fundamentals


Exam Ref DP-900 Microsoft Azure Data Fundamentals
By 作者:Daniel A. Seara and Francesco Milano
Publisher Finelybook 出版社 : Microsoft Press; 1st edition (6 Jun. 2021)
Language 语言: English
pages 页数: 336 pages
ISBN-10 书号: 0137252161
ISBN-13 书号 : 9780137252169
The Book Description robot was collected from Amazon and arranged by Finelybook
Prepare for Microsoft Exam DP-900―Demonstrate your real-world foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Fundamentals level.
Focus on the expertise measured by these objectives:

Describe core data concepts
Describe how to work with relational data on Azure
Describe how to work with non-relational data on Azure
Describe an analytics workload on Azure
This Microsoft Exam Ref:

Organizes its coverage by exam objectives
Features strategic, what-if scenarios to challenge you
Assumes you have foundational knowledge of core data concepts and their implementation with Microsoft
Azure data services, and are beginning to work with data in the cloud
About the Exam
Exam DP-900 focuses on core knowledge for describing fundamental database concepts and skills for cloud environments; cloud data services within Azure; cloud data roles, tasks, and responsibilities; Azure relational and non-relational data offerings, provisioning, and deployment; querying Azure relational databases; working with Azure non-relational data stores; building modern Azure data analytics solutions; and exploring Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight.
About Microsoft Certification
Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Fundamentals certification, demonstrating your understanding of the core capabilities of Azure data services and their use with relational data, non-relational data, and analytics workloads.

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