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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Implementing Data Engineering Solutions Using Microsoft Fabric |
| Exam Number: | DP-700 |
| Certificate Validity Period: | 1 year (renewable) |
| Passing Score: | 700/1000 |
| Exam Format: | Multiple choice, Case studies, Scenario-based questions, Multiple response |
| Exam Duration: | 100-120 |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Certified: Fabric Analytics Engineer Associate Microsoft Certified: Azure Data Engineer Associate |
| Available Languages: | French, Simplified Chinese, Spanish, Japanese, English, Korean, Portuguese (Brazil), German |
| Exam Price: | Varies by region (approx. $165 USD) |
| Recommended Training: | Microsoft Learn DP-700 Learning Path Microsoft Fabric Documentation |
| Exam Registration: | Microsoft Learn Certification Exam Page Pearson VUE Microsoft Exams |
| Sample Questions: | Microsoft DP-700 Sample Questions |
| Exam Way: | Online proctored via Pearson VUE or in-person at authorized testing centers |
| Pre Condition: | No formal prerequisites, but recommended experience with Azure data services and basic data engineering concepts |
| Official Syllabus URL: | https://learn.microsoft.com/credentials/certifications/exams/dp-700/ |
The Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) mock exams will allow you to prepare for the DP-700 exam in a smarter and faster way. You can improve your understanding of the DP-700 exam objectives and concepts with the easy-to-understand and actual DP-700 Exam Questions offered by ActualTestsQuiz. ActualTestsQuiz makes the DP-700 Practice Questions affordable for everyone and allows you to find all the information you need to polish your skills to be completely ready to clear the DP-700 exam on the first attempt.
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NEW QUESTION # 114
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns:
BikepointID
Street
Neighbourhood
No_Bikes
No_Empty_Docks
Timestamp
You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order.
Solution: You use the following code segment:
Does this meet the goal?
Answer: B
Explanation:
This code does not meet the goal because this is an SQL-like query and cannot be executed in KQL, which is required for the database.
Correct code should look like:
NEW QUESTION # 115
You need to recommend a method to populate the POS1 data to the lakehouse medallion layers.
What should you recommend for each layer? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
A screenshot of a computer Description automatically generated
Bronze Layer: A pipeline Copy activity
The bronze layer is used to store raw, unprocessed data. The requirements specify that no transformations should be applied before landing the data in this layer. Using a pipeline Copy activity ensures minimal development effort, built-in connectors, and the ability to ingest the data directly into the Delta format in the bronze layer.
Silver Layer: A notebook
The silver layer involves extensive data cleansing (deduplication, handling missing values, and standardizing capitalization). A notebook provides the flexibility to implement complex transformations and is well-suited for this task.
NEW QUESTION # 116
You need to create the product dimension.
How should you complete the Apache Spark SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
A screenshot of a computer Description automatically generated
Join between Products and ProductSubCategories:
Use an INNER JOIN.
The goal is to include only products that are assigned to a subcategory. An INNER JOIN ensures that only matching records (i.e., products with a valid subcategory) are included.
Join between ProductSubCategories and ProductCategories:
Use an INNER JOIN.
Similar to the above logic, we want to include only subcategories assigned to a valid product category. An INNER JOIN ensures this condition is met.
WHERE Clause
Condition: IsActive = 1
Only active products (where IsActive equals 1) should be included in the gold layer. This filters out inactive products.
NEW QUESTION # 117
You have a Fabric workspace that contains a lakehouse named Lakehousel. Lakehousel contains a table named Status_Target that has the following columns:
* Key
* Status
* LastModified
The data source contains a table named Status.Source that has the same columns as Status_Target. Status.
Source is used to populate Status_Target. In a notebook name Notebook!, you load Status_Source to a DataFrame named sourceDF and Status_Target to a DataFrame named targetDF. You need to implement an incremental loading pattern by using Notebook-!. The solution must meet the following requirements:
* For all the matching records that have the same value of key, update the value of LastModified in Status_Target to the value of LastModified in Status_Source.
* Insert all the records that exist in Status_Source that do NOT exist in Status_Target.
* Set the value of Status in Status_Target to inactive for all the records that were last modified more than seven days ago and that do NOT exist in Status.Source.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 118
You have a Fabric workspace that contains a write intensive warehouse named DW1. DW1 stores staging tables that are used to load a dimensional model. The tables are often read once, dropped, and then recreated to process new data.
You need to minimize load time of data from sources to staging tables in DW1.
What should you do?
Answer: D
NEW QUESTION # 119
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