DP-700 Implement and Manage an Analytics Solution Practice Question
Which approach is most efficient for loading a large volume of historical data into a Fabric Lakehouse from an external source?
⚠ Common exam trap
Candidates often suggest using 'Notebooks' or 'Dataflows' for initial large-scale loads, ignoring that the 'Copy' activity is purpose-built and optimized for high-throughput, parallel data ingestion.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the Data Factory Copy activity.
Efficient data ingestion is critical for minimizing pipeline duration and cloud compute costs. Using the Copy activity in Data Factory, which is optimized for high-throughput, parallel data transfer, is the industry standard for this task. Understanding how to use the correct integration tools prevents performance bottlenecks and ensures that large-scale data migration projects remain within their performance and budget windows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a Python script in a notebook to read and write rows one-by-one.
Why it's wrong here
Row-by-row processing is extremely slow and causes high overhead in a distributed environment like Spark. This method creates massive performance bottlenecks and will fail or time out on large datasets. Always leverage native bulk copy activities that are optimized for high-performance, parallelized data movement.
- ✓
Use the Data Factory Copy activity.
Why this is correct
The Copy activity in Data Factory is built specifically for high-throughput, parallelized data transfer. It automatically optimizes the connection and data movement, making it the most efficient way to load massive datasets into the Lakehouse while maintaining data integrity and reducing overall ingestion time.
- ✗
Download files locally and then upload them to the Fabric portal.
Why it's wrong here
Manual downloading and uploading is an inefficient, non-automated process that introduces significant latency and security risks. It is not feasible for large-scale data loads and fails to adhere to modern data engineering practices that prioritize automated, scalable, and secure data movement directly within the cloud infrastructure.
- ✗
Create a Power BI report and import the data.
Why it's wrong here
Power BI is a reporting tool, not a data ingestion or orchestration tool. Importing data through Power BI creates a hidden dataset that is difficult to manage or transform further. It is not designed to handle large-scale historical data loads into a Lakehouse and should not be used for this purpose.
About these practice questions
This DP-700 question is part of Courseiva's 152-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-700 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-700 exam.