DP-700 Practice Test 2025 (Fabric Data Engineer Associate)

DP-700 Practice Test Qs | Scripts to simulate lab | Concise, demo-driven explanation for right/wrong answer | Case Study

What you'll learn
- Clear the DP-700 Fabric Data Engineer Associate Exam in your first attempt
- Obtain the Fabric Data Engineer Associate badge
- Not just passively watch videos, but actively run scripts and learn to use Microsoft Fabric
- Perform lab demos of the administrative tasks required in the exam

Requirements
- Fundamental knowledge of any data and cloud
- A Free Fabric/Azure subscription

Description
<<The course is updated as per the skills measured on  April 21, 2025>>

WHY SHOULD YOU BUY MY DP-700 Fabric Data Engineer Associate MOCK TEST?

a. Deeply researched exam questions for DP 700. I create no more than one question/day to maintain high quality.

b. No simple one-liner questions. Each question is based on your understanding of a scenario. The questions challenge you tounderstand,apply, andanalyzeyour knowledge.

c. This course comes with both clear and lucidvideoandtextexplanations. The text explanations come with product illustrations for easy understanding. You can also go through the video explanations for a more seamless demo.

d. For each question I provide aPython Notebook/PowerQuery project file/scriptsto simulate the environment used in the question.

e. For each question I providea summarized versionof the answer (suitable for revisions) and a detailed answer (for in-depth learning).

f. I simulate the actual DP700 Fabric Data Engineer exam experience for you in the form ofdrag-and-drop questions,dropdown questions,multiple yes/no questions with a radio button,repeated scenario questions,etc.

g. Nodumpingof text in a ppt. PPTs are used only todemo architectureto enhance your understanding.

h. Explanations run parallel to the product. Every detailed explanation has corroborating evidence with the Microsoft product (like Microsoft Fabric) shown inscreenshots and clear callouts.

i. Explanations areNOT directly copiedfrom Microsoft documentation. I have rephrased all the reasoning in a simple and easy-to-understand language.

j. Nostep-motherlytreatment of incorrect answer choices. I took enough effort to explain the rationale for each answer choice (whether correct/wrong), including the reference links.

k. Don't worry aboutinaccurate sentence framing/wrong grammar/incorrect punctuation. I use Grammarly to review every question.

l. Almostnon-existent repetition of questionsonly to increase the question count.

m.I love to help you succeed. If you need to discuss, we have an Active Q&A dashboard and expect fast responses (save for my sleeping hours, which are generally less).

n. As soon as there is an update from Microsoft, I try toupdatemy course, keeping it always fresh.

o. The question bank ispeer-reviewedevery three months to ensure exam relevance.

p. Case Study: Contoware Analytics Modernization to help you better prepare for the exam.

The questions are collected from a variety of domains and sub-domains with extra care taken to equal attention to each exam area. Also, the questions are on different levels.

For example:

Remember-level questionstest whether you can recall memorized facts, & basic concepts.

Understand-level questionsvalidate whether you can explain the meanings of terms, & concepts.

Application-level questionstest whether you can perform tasks using facts, concepts, & techniques, and,

Analysis-level questionsvalidate whether you can diagnose situations & solve problems with concepts & techniques.

A mixture of questions at different levels reinforces your knowledge and prepares you to ace the exam.

These are the exam domains covered in the DP-700 practice exam:

Implement and manage an analytics solution (30–35%)

Configure Microsoft Fabric workspace settings

Configure Spark workspace settings

Configure domain workspace settings

Configure OneLake workspace settings

Configure data workflow workspace settings

Implement lifecycle management in Fabric

Configure version control

Implement database projects

Create and configure deployment pipelines

Configure security and governance

Implement workspace-level access controls

Implement item-level access controls

Implement row-level, column-level, object-level, and folder/file-level access controls

Implement dynamic data masking

Apply sensitivity labels to items

Endorse items

Implement and use workspace logging

Orchestrate processes

Choose between a pipeline and a notebook

Design and implement schedules and event-based triggers

Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions

Ingest and transform data (30–35%)

Design and implement loading patterns

Design and implement full and incremental data loads

Prepare data for loading into a dimensional model

Design and implement a loading pattern for streaming data

Ingest and transform batch data

Choose an appropriate data store

Choose between dataflows, notebooks, KQL, and T-SQL for data transformation

Create and manage shortcuts to data

Implement mirroring

Ingest data by using pipelines

Transform data by using PySpark, SQL, and KQL

Denormalize data

Group and aggregate data

Handle duplicate, missing, and late-arriving data

Ingest and transform streaming data

Choose an appropriate streaming engine

Choose between native storage, followed storage, or shortcuts in Real-Time Intelligence

Process data by using eventstreams

Process data by using Spark structured streaming

Process data by using KQL

Create windowing functions

Monitor and optimize an analytics solution (30–35%)

Monitor Fabric items

Monitor data ingestion

Monitor data transformation

Monitor semantic model refresh

Configure alerts

Identify and resolve errors

Identify and resolve pipeline errors

Identify and resolve dataflow errors

Identify and resolve notebook errors

Identify and resolve eventhouse errors

Identify and resolve eventstream errors

Identify and resolve T-SQL errors

Optimize performance

Optimize a lakehouse table

Optimize a pipeline

Optimize a data warehouse

Optimize eventstreams and eventhouses

Optimize Spark performance

Optimize query performance

Who this course is for:
- Students who want to clear the DP-700 Exam
- Students who want to obtain the Fabric Data Engineer Associate badge
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