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Microsoft DP-900日本語 Braindumps - in .pdf Free Demo

  • Exam Code: DP-900J
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Last Updated: Aug 02, 2026
  • Q & A: 320 Questions and Answers
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  • Exam Code: DP-900J
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900日本語版)
  • Last Updated: Aug 02, 2026
  • Q & A: 320 Questions and Answers
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Objective of Microsoft DP-900

The Microsoft Data Protection and Management Fundamentals exam is just one of the many exams dedicated to data management. Test your skills and knowledge in the area of data protection and management, as well as improve your skills. Pay attention to the latest changes in this field of technology. Skilling up to your skills, you must be aware of the latest changes in the technology field to become successful. Collection, integration, analysis and distribution of data is a great way to gain insight into the latest challenges in the field of data protection and management. Microsoft DP-900 exam dumps the most qualified candidates will be able to pass this exam easily. Accurate data collection, this data will be stored in a database. Integration of different systems, this data will be integrated with another database to analyze the data. Outline and analysis of data, also described in an outline. Distribution and distribution of data, this data will be sent to the correct locations and users for their use. Feedback and changes, the data will be analyzed for changes and feedback. Command and control, a command will be given to a list of specific users and systems to manipulate the data. Subscribe and receive data, the data will be sent to the appropriate users. Dashboards and reports and alerts, the data collected can be converted into a report or alert. Loading and storage and user access and BPA and cloud and networks and servers and operating systems, the candidates will increase their skills in data management.

Knowing how to process and use data is a very valuable skill in the modern IT world. Blob storage and data management, a quick and easy way to store files. Workflow and logic and data integration and export and SAP and SQL and SharePoint and webforms, the candidates will increase their skill in Microsoft cloud technologies. Solve problems and monitoring and forensics and management, the candidates will increase their skills in data protection. Outdated backups and DR solutions and paper backup and Oracle and Unix and security and virtualization, the candidates will increase their skills in data protection. Roles and responsibilities and training and policies and procedures, the candidates will increase their skills in data protection. Paid and volunteer and onsite and offsite and mobile and onsite and removable and disaster recovery and disaster recovery solutions, the candidates will increase their skills in data protection. Digital and paper and data and sensitive and compliance and eDiscovery, the candidates will increase their skills in data protection. Cognitive and user and cloud and non-volatile and network and mobile and software as a service and storage as a service, the candidates will increase their skills in data protection.

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Explain the Techniques Involved in Working with Relational Data on Microsoft Azure: 25-30%

  • Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.
  • Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.
  • Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.
  • Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

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Microsoft DP-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Describe considerations for working with non-relational data on Azure15-20%- Describe non-relational Azure data services
  • 1. Describe Azure Blob storage
  • 2. Describe Azure Table storage
  • 3. Describe Azure Cosmos DB
  • 4. Describe Azure File storage
- Describe non-relational concepts
  • 1. Describe non-relational data offerings
  • 2. Identify non-relational data
Identify considerations for relational data on Azure20-25%- Describe relational Azure data services
  • 1. Describe Azure SQL Managed Instance
  • 2. Describe Azure SQL family of products
  • 3. Describe SQL Server on Azure Virtual Machines
  • 4. Describe Azure Database for PostgreSQL
  • 5. Describe Azure SQL Database
  • 6. Describe Azure Database for MySQL
  • 7. Describe Azure Database for MariaDB
- Describe relational concepts
  • 1. Describe normalization
  • 2. Identify features of relational data
Describe core data concepts25-30%- Identify options for data storage
  • 1. Describe types of databases
  • 2. Describe common formats for data files
- Describe ways to represent data
  • 1. Describe features of structured data
  • 2. Describe features of unstructured data
  • 3. Describe features of semi-structured data
Describe an analytics workload on Azure25-30%- Describe data visualization in Microsoft Power BI
  • 1. Describe Power BI reports and dashboards
  • 2. Describe Power BI
  • 3. Describe Power BI tools and workflow
- Describe analytics concepts
  • 1. Describe data warehousing
  • 2. Describe analytical workloads
  • 3. Describe ETL and ELT processes
  • 4. Describe transactional workloads
- Describe Azure data analytics services
  • 1. Describe Azure Databricks
  • 2. Describe Azure Data Factory
  • 3. Describe Microsoft Fabric
  • 4. Describe Azure Stream Analytics
  • 5. Describe Azure HDInsight
  • 6. Describe Azure Synapse Analytics

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