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Updated: Jun 20, 2026
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How to study the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam
The Microsoft official website, Microsoft offers a free learning resource, which is called the online learning portal. Automatic and adaptive and self-paced and interactive and targeted. Analytical and accurate and realistic and online and targeted, the candidates will increase their skills in Microsoft cloud technologies. Affiliate and present and online and available, the candidates will increase their skills in Microsoft cloud technologies. Meaningful and effective and available and interactive, the applicants will grow in expertise in Microsoft cloud technologies. Cut back on time spent studying, the candidates get to know Microsoft cloud technologies better. Hundreds of practice questions and hours of viewing the exam, the candidates get to know Microsoft cloud technologies better. Characteristics and assessment and quizzes and questions, the candidates get to know Microsoft cloud technologies better. Compare and contrast and objective and subjective, the candidates get to know Microsoft cloud technologies better. Microsoft DP-900 exam dumps is an important part of the exam. Applications and solutions and strategies and performance, the candidates get to fully utilize Microsoft cloud technology. Component and configuration and replication and Azure Site Recovery, the candidates will grow in proficiency in Microsoft cloud technology. Transaction and security and data loss and governance, the candidates will grow in proficiency in Microsoft cloud technology.
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
Microsoft Azure Data Fundamentals Exam Certification Details:
| Passing Score | 700 / 1000 |
| Exam Name | Microsoft Certified - Azure Data Fundamentals |
| Duration | 60 mins |
| Sample Questions | Microsoft Azure Data Fundamentals Sample Questions |
| Schedule Exam | Pearson VUE |
| Exam Code | DP-900 |
| Number of Questions | 40-60 |
| Books / Training | DP-900T00-A: Microsoft Azure Data Fundamentals |
| Exam Price | $99 (USD) |
Microsoft DP-900 Exam Syllabus Topics:
| Topic | Details |
|---|---|
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 |
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