Microsoft · 2026 Edition
A complete preparation guide written by Microsoft-certified engineers. Covers the exam format,all 4 blueprint domains, a week-by-week study plan, and proven tips for passing first time.
2–4 weeks
Prep time
Beginner
Difficulty
50
Exam questions
700/1000
Pass mark
Exam code
DP-900
Full name
Microsoft Azure Data Fundamentals
Vendor
Microsoft
Duration
60 minutes
Questions
50 items
Passing score
700/1000 (scaled)
Domains covered
4 blueprint domains
Recommended experience
No prerequisites — suitable for beginners to data and cloud
Typical prep time
2–4 weeks
DP-900 validates foundational knowledge of data concepts and how they are implemented on Azure. It is useful for data analysts, developers, and administrators starting to work with Azure data services.
Job roles this opens
Domain percentage weights are not currently available for this exam. The checklist below is still useful for planning your study.
Week 1
Core Data Concepts: relational vs non-relational, batch vs streaming, data roles
Tip: Know the three data professional roles: Database Administrator (manages databases, security, backup), Data Engineer (builds data pipelines and storage solutions), Data Analyst (queries and visualises data for insights). Questions describe a task and ask which role performs it.
Week 2
Relational Data on Azure: Azure SQL Database, Azure SQL Managed Instance, SQL concepts
Tip: Relational database concepts tested: tables, rows, columns, primary key, foreign key, normalisation, and how indexes improve query performance. Basic SQL vocabulary (SELECT, WHERE, JOIN) is expected without complex query writing.
Week 3
Non-Relational Data on Azure: Cosmos DB, Azure Table Storage, Blob Storage, Data Lake
Tip: Know the non-relational data types: key-value (Azure Table Storage), document (Cosmos DB JSON), column-family (Cosmos DB Cassandra API), graph (Cosmos DB Gremlin API). Questions describe a data structure and ask which type fits.
Week 4
Analytics on Azure: Synapse Analytics, Data Factory, Azure Databricks, Power BI
Tip: Know the analytics pipeline flow: Data Factory (ingest/orchestrate) → Data Lake/Synapse (store/process) → Power BI (visualise). Questions describe a role in the pipeline and ask which Azure service performs it.
DP-900 is conceptual. You will not write SQL queries from scratch or configure Azure services — questions test what each service does and which service fits a given scenario.
Batch vs streaming data is a core concept: batch processing handles data in groups on a schedule (nightly sales reports), stream processing handles data in real time (fraud detection on transactions). Know which Azure service is used for each.
Structured vs semi-structured vs unstructured data: relational databases hold structured data, JSON/XML is semi-structured, and images/video/audio are unstructured. Azure Blob Storage and Data Lake hold unstructured and semi-structured data at scale.
Azure Cosmos DB supports multiple APIs: SQL/Core, MongoDB, Cassandra, Gremlin, Table. Questions describe a developer using a specific API and ask which Cosmos DB API they are using.
Power BI concepts tested on DP-900: reports (visualisations), dashboards (pinned visuals from multiple reports), datasets (the data source), workspaces (collaboration areas). Know the difference between Power BI Desktop (free, for creating reports) and Power BI Service (cloud, for sharing).
Apply everything in this guide with adaptive practice questions, detailed answer explanations, and domain analytics.
Deep-dive explanations of the key topics tested on DP-900 — with exam key points and common misconceptions.