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.
See full details at:
www.microsoft.com/learn
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Für Beruf und Forschung
Für höhere Schule und Studium
Maße
Höhe: 231 mm
Breite: 188 mm
Dicke: 20 mm
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ISBN-13
978-0-13-725216-9 (9780137252169)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Daniel A. Seara is an experienced software developer. He has more than 20 years' experience as a technical instructor, developer, and development consultant. Daniel has worked as a software consultant in a wide range of companies in Argentina, Spain, and Peru. He has been asked by Peruvian Microsoft Consulting Services to help several companies in their migration path to .NET Framework development.
Daniel was Argentina's Microsoft Regional Director for 4 years and was the first nominated Global Regional Director, a position he held for two years. He was also the manager of the De-sarrollador Cinco Estrellas I (Five-Star Developer) program, one of the most successful training projects in Latin America. Daniel held a Visual Basic MVP status for more than 10 years, as well as a SharePoint Server MVP status from 2008 until 2014. Additionally, Daniel is the founder and "Dean" of Universidad .NET, the most visited Spanish language site on which to learn .NET. In 2005, he joined Lucient, the leading global company on the Microsoft Data Platform, where he has been working as a trainer, consultant, and mentor.
Francesco Milano has been working with Microsoft technologies since 2000. Francesco specializes in the .NET Framework and SQL Server platform, and he focuses pri-marily on back-end development, integration solutions, relational model design, and imple-mentation. Since 2013 Francesco has also been exploring emerging trends and technologies pertaining to the big data and advanced analytics world, consolidating his knowledge of products like Azure HDInsight, Databricks, Azure Data Factory, and Azure Synapse Analytics.
Francesco is a speaker at prominent Italian data platform conferences and workshops. In 2015, he joined Lucient, the leading global company on the Microsoft Data Platform, where he has been working as a trainer, consultant, and mentor.
Introduction
CHAPTER 1 Describe core data concepts
CHAPTER 2 Describe how to work with relational data on Azure
CHAPTER 3 Describe how to work with non-relational data on Azure
CHAPTER 4 Describe an analytics workload on Azure
