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How to book the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Step 1: Visit Microsoft Learning and search for DP-900: Microsoft Azure fundamentals.
  • Step 2: Sign up/log in to the Pearson VUE account
  • Step 3: Select a local center based on your country, date, time and confirm with a payment method.

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What job roles can you pursue after passing the Microsoft DP-900 exam?

Microsoft Certified: Azure Data Fundamentals is an entry-level certificate. However, the candidates who pass the prerequisite exam and obtain this certification can pursue a variety of rewarding job roles. These include an IT Administrator, a Desktop Engineer, a Windows Administrator, an Azure Security Engineer, an Azure Solutions Architect, an Azure Application Architect, a Technical Help Desk, and an IT Service Desk Analyst, among others. The salary outlook for these positions is an average of $56,000 per annum.

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

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Introduction to Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.

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Skills measured

  • Describe an analytics workload on Azure (25-30%)
  • Describe how to work with relational data on Azure (25-30%)
  • Describe core data concepts (15-20%)
  • Describe how to work with non-relational data on Azure (25-30%)

Microsoft DP-900日本語 Exam Syllabus Topics:

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

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