DP-900: Azure Data Fundamentals Certification Training
Microsoft’s entry point into working with data on Azure — relational and non-relational data, analytics workloads, and the core services behind them. Vendor-agnostic foundations that carry over to any cloud platform.
Find Your Path
Considering DP-900? Speak with our team first.
Fill in the form below and we will arrange a personal consultation to walk you through what DP-900 covers, who it is designed for, and whether it aligns with your goals — at no cost, and with no obligation to enroll.
Prerequisites
DP-900 has no formal prerequisites, but candidates typically bring:
- Basic familiarity with the concepts of relational and non-relational data
- Some awareness of data workload types — transactional versus analytical
- No coding or hands-on database administration background required to start
- Curiosity about how organizations store, process, and analyze data at scale
Skills You’ll Gain
DP-900 Syllabus — Detailed Topics
Click any topic to expand.
Core Data Concepts
The foundational vocabulary every other topic in this course builds on:
- Structured, semi-structured, and unstructured data — what separates them
- Common data file formats and data stores, including databases
- Identifying the right Azure datastore for common use cases
- Transactional versus analytical data workloads
- Roles and responsibilities — database administrators, data engineers, data analysts
Relational Data on Azure
The most common data pattern in business systems, and how Azure handles it:
- Core features of relational data and why normalization matters
- Common SQL statements and database objects
- The Azure SQL family — Azure SQL Database, SQL Managed Instance, SQL Server on Azure VMs
- Azure database services for open-source database systems
Non-Relational Data on Azure
Where relational databases fall short, and what Azure offers instead:
- Azure Blob storage, Azure Files, and Azure Table storage — features and use cases
- Capabilities of Azure Cosmos DB
- Azure Cosmos DB APIs and when to use each
Analytics Workloads on Azure
Turning raw data into something an organization can actually use:
- Data ingestion and processing considerations at scale
- Analytical data store options
- Azure Databricks and Microsoft Fabric for large-scale analytics
- Batch versus streaming data — the real-time analytics distinction
- Data visualization fundamentals in Power BI
Skills Measured
Audience Profile
This exam is intended for candidates beginning to work with data in the cloud. You should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical. DP-900 can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.
Describe core data concepts25–30%
Describe ways to represent data
- Features of structured data
- Features of semi-structured data
- Features of unstructured data
Identify options for data storage
- Common formats for data files
- Features of common data stores, including databases
- Azure datastores for common use cases
Describe common data workloads
- Features of transactional workloads
- Features of analytical workloads
Identify roles and responsibilities for data workloads
- Responsibilities for database administrators
- Responsibilities for data engineers
- Responsibilities for data analysts
Identify considerations for relational data on Azure20–25%
Describe relational concepts
- Features of relational data
- Normalization and why it is used
- Common SQL statements
- Common database objects
Describe relational Azure data services
- The Azure SQL family — Azure SQL Database, Azure SQL Managed Instance, SQL Server on Azure Virtual Machines
- Azure database services for open-source database systems
Describe considerations for working with non-relational data on Azure15–20%
Describe the capabilities of Azure storage
- Features of Azure Blob storage
- Features of Azure Files
- Features of Azure Table storage
Describe the capabilities and features of Azure Cosmos DB
- Use cases for Azure Cosmos DB
- Azure Cosmos DB APIs
Describe an analytics workload on Azure25–30%
Describe common elements of large-scale analytics
- Considerations for data ingestion and processing
- Options for analytical data stores
- Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft Fabric
Describe considerations for real-time data analytics
- The difference between batch and streaming data
- Microsoft cloud services for real-time analytics
Describe data visualization in Microsoft Power BI
- Capabilities of Power BI
- Features of data models in Power BI
- Appropriate visualizations for data
Why This Certification Matters
Almost every AI and analytics initiative eventually runs into the same question: where does the data actually live, and is it structured in a way that supports what you’re trying to do? DP-900 is the credential that means someone doesn’t have to ask that question from scratch — it builds a shared vocabulary around relational versus non-relational data, transactional versus analytical workloads, and where each fits on Azure.
It’s deliberately vendor-agnostic in spirit — the underlying concepts (normalization, structured versus unstructured data, batch versus streaming) apply well beyond Azure, which makes this a durable foundation rather than a narrow product certification.
It’s also explicitly built as an on-ramp — Microsoft positions DP-900 as useful preparation (though not a formal prerequisite) for the Azure Database Administrator Associate and Azure Data Engineer Associate certifications, making it a natural first step for anyone eyeing a data-focused Azure career.
Flexible by design. Delivery format and pacing adjust to the audience — a compact cohort format for corporate teams, and an extended, exam-prep-paced format for students and individual learners. Talk to us about what fits.
Frequently Asked Questions
Do I need coding or SQL experience for DP-900?
No formal experience is required to start. The exam does expect familiarity with common SQL statements, which is covered as part of the training — you don’t need to already know how to write queries beforehand.
Is DP-900 only useful if I plan to work with Azure specifically?
No. The underlying data concepts — relational versus non-relational data, transactional versus analytical workloads, batch versus streaming — are widely applicable across cloud platforms, not just Azure.
Is DP-900 a prerequisite for Azure Data Engineer certification?
No, it’s not a formal prerequisite, but Microsoft explicitly recommends it as useful preparation for both Azure Database Administrator Associate and Azure Data Engineer Associate paths.
What should I do after DP-900?
Many learners progress toward Azure Database Administrator Associate or Azure Data Engineer Associate, depending on whether their interest is in managing databases or building data pipelines and analytics solutions.
Enroll in Certification Training
The full paid training program — format and duration vary by audience. This is separate from the complimentary consultation above.