- ホーム
- > 洋書
- > 英文書
- > Computer / General
Full Description
Prepare for Microsoft Exam DP-500 and demonstrate your real-world ability to design, create, and deploy enterprise-scale data analytics solutions. Designed for business intelligence developers, architects, data analysts, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Enterprise Data Analyst Associate level.
Focus on the expertise measured by these objectives:
Implement and manage a data analytics environment
Query and transform data
Implement and manage data models
Explore and visualize data
This Microsoft Exam Ref:
Organizes its coverage by exam objectives
Features strategic, what-if scenarios to challenge you
Assumes you are a business intelligence developer, architect, data engineer, data architect, data analyst, or another professional with Power BI and Azure experience.
About the Exam
Exam DP-500 focuses on knowledge needed to govern and administer data analytics environments; integrate analytics platforms into existing IT infrastructure; manage the analytics development lifecycle; query data with Azure Synapse Analytics; ingest and transform data with Power BI; design and build tabular models; optimize enterprise-scale data models; explore data with Azure Synapse Analytics; and visualize data with Power BI.
About Microsoft Certification
Passing this exam fulfills your requirements for the Microsoft Certified: Azure Enterprise Data Analyst Associate certification, demonstrating your knowledge of designing, creating, and deploying enterprise-scale data analytics solutions. Responsibilities include performing advanced data analytics at scale, collecting enterprise-level requirements for data analytics solutions that include Azure and Microsoft Power BI, advising on data governance and configuration for Power BI administration, monitoring data usage, and optimizing solution performance.
See full details at: microsoft.com/learn
Contents
CHAPTER 1 Implement and manage a data analytics environment
CHAPTER 2 Query and transform data
CHAPTER 3 Implement and manage data models
CHAPTER 4 Explore and visualize data
