Microsoft Azure Data Fundamentals (DP-900) Practice Exam

Microsoft Azure Data Fundamentals (DP-900) Practice Exam

Microsoft Azure Data Fundamentals (DP-900) helps the candidates in demonstrating their knowledge of core data concepts and related Microsoft Azure data services. Candidates for this exam must have familiarity with Exam DP-900’s self-paced or instructor-led learning material.

Who should take the DP-900 Exam?

Microsoft Azure Data Fundamentals (DP-900) exam is intended for you if you’re a candidate beginning to work with data in the cloud and have familiarity with:

• The concepts of relational and non-relational data.
• Different types of data workloads such as transactional or analytical.

Exam Details of Microsoft DP-900 

• Exam Code: DP-900
• Exam Name: Microsoft Azure Data Fundamentals
• Exam Languages: English, Japanese, Chinese (Simplified), Korean, French, German, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian
• Exam Questions: 40-60 Questions
• Passing Score: 700 or greater (On a scale 1 - 1000)

DP-900 Exam Course Outline 

The Microsoft DP-900 Exam covers the given topics  - 

Domain 1: Explaining core data concepts (25–30%)

Describing ways to represent data

• Explaining features of structured data
• Describing features of semi-structured
• Explaining features of unstructured data

Identifying options for data storage

• Describing common formats for data files
• Explaining types of databases

Explain common data workloads

• Describing features of transactional workloads
• Explain features of analytical workloads

Discover roles and responsibilities for data workloads

• Describing responsibilities for database administrators
• Explain responsibilities for data engineers
• Describing responsibilities for data analysts

Domain 2: Identifying considerations for relational data on Azure (20–25%)

Describing relational concepts

• Identifying features of relational data
• Describing normalization and why it is used
• Discover common structured query language (SQL) statements
• Identifying common database objects

Describing relational Azure data services

• Explaining the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
• Identifying Azure database services for open-source database systems

Domain 3: Explaining considerations for working with non-relational data on Azure (15–20%)

Describing the capabilities of Azure storage

• Describing Azure Blob storage
• Describing Azure File storage
• Explain Azure Table storage

Explaining capabilities and features of Azure Cosmos DB

• Identifying use cases for Azure Cosmos DB
• Describing Azure Cosmos DB APIs

Domain 4: Describing an analytics workload on Azure (25–30%)

Explain common elements of large-scale analytics

• Describing considerations for data ingestion and processing
• Describing options for analytical data stores
• Explaining Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, Azure HDInsight, and Azure Data Factory

Describing consideration for real-time data analytics

• Explaining the difference between batch and streaming data
• Identifying Microsoft cloud services for real-time analytics

Explain data visualization in Microsoft Power BI

• Identifying capabilities of Power BI
• Describing features of data models in Power BI
• Discover appropriate visualizations for data