Exam Ref DP-900 Microsoft Azure Data Fundamentals
- Part of the Exam Ref series.
Book
- List price: $39.99
eBook
- List price: $31.99
Book + eBook
- Your price: $43.19
- List price: $71.98
More Purchase Options
This title is also available bundled with a practice test.
- Published 4/6/2021
- 1st Edition
- 336 pages
- Book 978-0-13-725216-9
- eBook 978-0-13-725205-3
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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