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MicrosoftDP-900FoundationalDataAvailable

Microsoft Azure Data Fundamentals

Core data concepts, relational and non-relational data on Azure, and analytics workloads with Microsoft Fabric, Databricks and Power BI.

Independent practice — not affiliated with or endorsed by Microsoft. DP-900 is used only to identify the exam. Trademark notices

Official objectives ↗Official exam page ↗
Workspace DP-900
Questions
45
Scored · unscored
45 · 0
Time
45 min
Passing score
700 on 1–1000
ESL accommodation
+30 min

Domain weights

Share of scored content per domain. Every sitting draws questions by these weights.

  1. D1Describe core data concepts28 %23 concepts
  2. D2Identify considerations for relational data on Azure23 %20 concepts
  3. D3Describe considerations for working with non-relational data on Azure19 %17 concepts
  4. D4Describe an analytics workload30 %24 concepts

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Full exam simulation

45 questions · 45 minutes, 0 unscored and not identified. One question per screen, flag and strike-out, a review screen and a score report per domain — no answers until you finish.

ESL +30

The full sitting with 30 extra minutes (75 min) — the accommodation non-native English speakers can request for exams in English.

Quick 20

20 questions · 20 min, same weights, all scored. A daily check.

Weak spots

20 questions aimed at your weakest domains, missed concepts and due reviews.

Practice builder

Pick domains, topics, how many questions and which pool (new, wrong, due, low confidence). Spaced repetition with confidence ratings, flashcards and a mistake book.

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Domain drill

One domain, up to 20 questions.

Downloads this exam's questions so practice works without a connection.

What's on the exam

  1. Domain 1: Describe core data concepts

    28 %

    Structured, semi-structured and unstructured data; file formats (CSV, JSON, Parquet, Avro, ORC); databases and Azure data stores; transactional versus analytical workloads; the roles of database administrators, data engineers and data analysts. Official range 25–30 %.

    Practice domain 1 →

  2. Domain 2: Identify considerations for relational data on Azure

    23 %

    Relational features, normalization, common SQL statements (DDL, DML, DCL) and database objects such as views, indexes and stored procedures; the Azure SQL family and Azure Database for PostgreSQL and MySQL. Official range 20–25 %.

    Practice domain 2 →

  3. Domain 3: Describe considerations for working with non-relational data on Azure

    19 %

    Azure Blob storage (access tiers, Data Lake Storage Gen2), Azure Files and Azure Table storage; Azure Cosmos DB use cases, global distribution and its APIs (NoSQL, MongoDB, PostgreSQL, Apache Cassandra, Apache Gremlin, Table). Official range 15–20 %.

    Practice domain 3 →

  4. Domain 4: Describe an analytics workload

    30 %

    Data ingestion and processing (ETL and ELT), analytical stores (data warehouse, data lake, lakehouse), Azure Databricks and Microsoft Fabric; batch versus streaming and real-time analytics; Power BI capabilities, data models and choosing visualizations. Official range 25–30 %.

    Practice domain 4 →

Domain names and weights come from the official DP-900 exam objectives (checked 2026-10-28). Always check it for the authoritative scope.

Includes 13 performance-style items (put in order, match, read an exhibit) — practice them with the “Order / match” filter.

The real exam's full hot-area simulations (labs in a live interface) are not reproduced.

Sources · checked 2026-10-28
Official objectives ↗Official exam page ↗

Sample questions

Two of this exam's original questions, with the explanation you get after every answer.

Sample 1Select one

A retailer stores customer records where every row has the same columns: CustomerID, Name, City and Email. How is this data classified?

  • ASemi-structured data described by tags inside each record
  • BStreaming data that arrives as a series of events
  • CUnstructured data stored as binary large objects
  • DStructured data with a fixed schema of rows and columns
Show answer & explanation

Correct: D. Structured data follows a fixed schema: every row has the same columns with defined data types, which is how relational tables store data.

Sample 2Select 2

Which TWO formats store data in a columnar layout that suits analytical queries? (Select TWO.)

  • AOptimized Row Columnar (ORC)
  • BJSON Lines
  • CApache Parquet
  • DComma-separated values (CSV)
  • EApache Avro
Show answer & explanation

Correct: A, C. Parquet and ORC organize values by column, so analytical engines read only the columns a query needs and compress repeated values well.

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Not affiliated with, endorsed by or sponsored by Amazon Web Services, Linux Professional Institute, CompTIA, Microsoft, HashiCorp, Google Cloud, CNCF / Linux Foundation, ISC2, PeopleCert (ITIL), Oracle, MongoDB. AWS and the AWS exam names are trademarks of Amazon.com, Inc. or its affiliates. LPI, Linux Essentials and LPIC are trademarks of the Linux Professional Institute. Linux is a registered trademark of Linus Torvalds. CompTIA, A+, Network+, Security+, CySA+ and Linux+ are trademarks of CompTIA, Inc. Microsoft, Azure, Microsoft Entra, Microsoft Defender, Microsoft Sentinel, Microsoft Purview and Microsoft Foundry are trademarks of the Microsoft group of companies. HashiCorp, Terraform and HCP are trademarks of HashiCorp, an IBM company. Google Cloud, Gemini and Vertex AI are trademarks of Google LLC. Kubernetes, KCNA and CNCF are trademarks of The Linux Foundation. ISC2, CC and Certified in Cybersecurity are trademarks of ISC2, Inc. ITIL and PRINCE2 are registered trademarks of PeopleCert. Practice questions are original and not endorsed by PeopleCert. Oracle, Oracle Database and SQL*Plus are trademarks of Oracle and/or its affiliates. Practice questions are original and not endorsed by Oracle. MongoDB, Atlas and Compass are trademarks of MongoDB, Inc. Practice questions are original and not endorsed by MongoDB. Exam names are used here only to identify the exams. Questions are original practice material, not real exam content.