Microsoft Azure Data Fundamentals : DP-900 Exam Questions

  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Jun 01, 2026
  • Q&As: 316 Questions and Answers

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About Microsoft Azure Data Fundamentals Exam Braindumps

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

  • Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.
  • Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.
  • Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.

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Workload analytics on Azure

  • Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.
  • Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.
  • Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.
  • Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.

Microsoft DP-900 Exam Syllabus Topics:

TopicDetails

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 family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
- 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 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 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, encryption)
- 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 Storage Gen2, 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

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

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