Welcome to Microsoft Azure Data Fundamentals DP-900 practice tests. This course will help you to test your preparation before attempting the certification exam.

• The questions are as per the DP-900 exam syllabus of the official documentation.

• There are 2 Full-Length Practice tests with unique and high-quality questions. The third test contains 34+ questions.

• We update these tests by adding new questions and additional practice tests - up to 6 practice tests (Max allowed by Udemy)

• 100% Exam Coverage - Tests are updated regularly to keep them up to date with the current syllabus.

• Retake Endlessly: You can retake as many times as you need.

• Detail Explanations: You get detailed explanations for all the answers with reference links and official documentation.

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Exam DP-900: Microsoft Azure Data Fundamentals:-

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Describe core data concepts (15-20%)

Describe types of core data workloads

• Describe batch data

• Describe streaming data

• Describe the difference between batch and streaming data

• Describe the characteristics of relational data

Describe data analytics core concepts

• Describe data visualization (e.g., visualization, reporting, business intelligence (BI))

• Describe basic chart types such as bar charts and pie charts

• Describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive)

• Describe ELT and ETL processing

• Describe the concepts of data processing

Describe how to work with relational data on Azure (25-30%)

Describe relational data workloads

• Identify the right data offering for a relational workload

• Describe relational data structures (e.g., tables, index, views)

Describe relational Azure data services

• Describe and compare PaaS, IaaS, and SaaS solutions

• Describe Azure SQL database services including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machine

• Describe Azure Synapse Analytics

• Describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL

Identify basic management tasks for relational data

• Describe provisioning and deployment of relational data services

• Describe a method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)

• Identify data security components (e.g., firewall, authentication)

• Identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)

• Identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.)

Describe query techniques for data using SQL language

• Compare Data Definition Language (DDL) versus Data Manipulation Language (DML)

• Query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL

Describe how to work with non-relational data on Azure (25-30%)

Describe non-relational data workloads

• Describe the characteristics of non-relational data

• Describe the types of non-relational and NoSQL data

• Recommend the correct data store

• Determine when to use non-relational data

Describe non-relational data offerings on Azure

• Identify Azure data services for non-relational workloads

• Describe Azure Cosmos DB APIs

• Describe Azure Table storage

• Describe Azure Blob storage

• Describe Azure File storage

Identify basic management tasks for non-relational data

• Describe provisioning and deployment of non-relational data services

• Describe a method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)

• Identify data security components (e.g., firewall, authentication)

• Identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)

• Identify management tools for non-relational data

  
  

Describe an analytics workload on Azure (25-30%)

Describe analytics workloads

• Describe transactional workloads

• Describe the difference between a transactional and an analytics workload

• Describe the difference between batch and real-time

• Describe data warehousing workloads

• Determine when a data warehouse solution is needed

Describe the components of a modern data warehouse

• Describe Azure data services for modern data warehousing such as Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight

• Describe modern data warehousing architecture and workload

Describe data ingestion and processing on Azure

• Describe common practices for data loading

• Describe the components of Azure Data Factory (e.g., pipeline, activities, etc.)

• Describe data processing options (e.g., Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)

Describe data visualization in Microsoft Power BI

• Describe the role of paginated reporting

• Describe the role of interactive reports

• Describe the role of dashboards

• Describe the workflow in Power BI