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Microsoft DP-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Describe considerations for working with non-relational data on Azure | 15–20% | - Describe non-relational data concepts
|
| Identify considerations for relational data on Azure | 20–25% | - Describe Azure relational data services
|
| Describe core data concepts | 25–30% | - Describe types of data
|
| Describe an analytics workload on Azure | 25–30% | - Describe real-time analytics
|
Questions About the Microsoft Azure Data Fundamentals Package
The Microsoft Azure Data Fundamentals exam requires a score of 700 / 1000 to pass, and the official registration fee is $99 USD. Knowing these numbers in advance keeps your planning honest.
Each round of the DP-900 question bank starts from the official exam objectives: experts map the syllabus, draft questions to cover it with precision, and review the result before release. When new exam points appear, the bank is updated accordingly — deliberate coverage, not guesswork.
Any details you leave with us during browsing or purchase are guarded against misuse and external threats, and they are used only to deliver your order and support. Your DP-900 purchase stays between you and us — that is a standing commitment, not a marketing line.
The Microsoft Azure Data Fundamentals exam contains 40–60 questions, and you will have 60 minutes minutes to complete them. Practicing under the same constraints makes exam-day pacing feel rehearsed.
No prerequisites required
You can confirm the current eligibility requirements on the official DP-900 exam page before you register.
Many candidates combine practice questions with official training. Recommended options include:
This package includes 340 practice questions for the Microsoft Azure Data Fundamentals exam. Every answer is verified by an experienced team of experts, so you can trust what you study.
You can register for the Microsoft Azure Data Fundamentals exam through the official channels:
The Microsoft Azure Data Fundamentals practice questions are organized around the official exam objectives. Key topics include:
- Describe an analytics workload on Azure (25–30%)
- Identify considerations for relational data on Azure (20–25%)
- Describe considerations for working with non-relational data on Azure (15–20%)
Syllabus-driven coverage means no wasted practice on irrelevant material.
Microsoft Azure Data Fundamentals Sample Questions:
You have data saved in the following format.
\
Which format was used?
- A. JSON
- B. yaml
- C. XML
- D. HTML
Correct Answer: A 🗳️
Your company needs to design a database that illustrates the relationships between utilization levels of individual network devices across a local area network.
Which type of data store should you use?
- A. key/value
- B. document
- C. columnar
- D. graph
Correct Answer: D 🗳️
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For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: Yes
Azure Data Studio is a cross-platform database tool for data professionals using on-premises and cloud data platforms on Windows, macOS, and Linux.
You can use Azure Data Studio to connect to an Azure SQL Database server. You ' ll then run Transact-SQL (T-SQL) statements to create and query Azure SQL databases.
Box 2: No
SQL Server Management Studio is for configuring, managing, and administering all components within Microsoft SQL Server, not to create SQL notebooks.
Instead use Azure Data Studio to create SQL notebook.
Box 3: Yes
You can use the Azure Data Studio to restore databases.
Reference:
https://docs.microsoft.com/en-us/sql/azure-data-studio/what-is-azure-data-studio
You have the following SQL query.
NOTE: Each correct selection is worth one point.
Correct Answer:
What are three characteristics of an Online Transaction Processing (OLTP) workload? Each correct answer presents a complete solution. (Choose three.) NOTE: Each correct selection is worth one point.
- A. heavy writes and moderate reads
- B. schema defined in a database
- C. normalized data
- D. light writes and heavy reads
- E. denormalized data
- F. schema defined when reading unstructured data from a database
Correct Answer: A,B,E 🗳️
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