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Microsoft DP-700 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | Implementing Data Engineering Solutions Using Microsoft Fabric |
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| Exam Number: | DP-700 |
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| Real Exam Qty: | 50 - 60 |
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| Passing Score: | 700 / 1000 |
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| Related Certifications: | Microsoft Certified: Fabric Data Engineer Associate |
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| Exam Price: | $165 USD |
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| Certificate Validity Period: | 12 Months (Renewable annually) |
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| Available Languages: | French, Japanese, English, German, Portuguese (Brazil), Simplified Chinese, Spanish |
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| Exam Format: | Multiple choice, Scenario-based, Drag-and-drop, Case studies |
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| Exam Duration: | 100 minutes |
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| Sample Questions: | Microsoft DP-700 Sample Questions |
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| Exam Way: | Online proctored or Test center |
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| Pre Condition: | No specific prior certification required. |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-700/ |
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| Topic | Details |
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| Topic 1 | - Ingest and transform data: This section of the exam measures the skills of Data Engineers that cover designing and implementing data loading patterns. It emphasizes preparing data for loading into dimensional models, handling batch and streaming data ingestion, and transforming data using various methods. A skill to be measured is applying appropriate transformation techniques to ensure data quality.
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| Topic 2 | - Monitor and optimize an analytics solution: This section of the exam measures the skills of Data Analysts in monitoring various components of analytics solutions in Microsoft Fabric. It focuses on tracking data ingestion, transformation processes, and semantic model refreshes while configuring alerts for error resolution. One skill to be measured is identifying performance bottlenecks in analytics workflows.
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| Topic 3 | - Implement and manage an analytics solution: This section of the exam measures the skills of Microsoft Data Analysts regarding configuring various workspace settings in Microsoft Fabric. It focuses on setting up Microsoft Fabric workspaces, including Spark and domain workspace configurations, as well as implementing lifecycle management and version control. One skill to be measured is creating deployment pipelines for analytics solutions.
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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q116-Q121):
NEW QUESTION # 116
HOTSPOT
You have an Azure Event Hubs data source that contains weather data.
You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the destination.
You need to batch ingest only rows from the data source where the City attribute has a value of Kansas. The filter must be added before the destination. The solution must minimize development effort.
What should you use for the data processor and filtering? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

NEW QUESTION # 117
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1.
You plan to deploy Warehouse1 to a new workspace named Workspace2.
As part of the deployment process, you need to verify whether Warehouse1 contains invalid references. The solution must minimize development effort.
What should you use?
- A. a database project
- B. a T-SQL script
- C. a deployment pipeline
- D. a Python script
Answer: C
NEW QUESTION # 118
You have a Fabric F32 capacity that contains a workspace. The workspace contains a warehouse named DW1 that is modelled by using MD5 hash surrogate keys.
DW1 contains a single fact table that has grown from 200 million rows to 500 million rows during the past year.
You have Microsoft Power BI reports that are based on Direct Lake. The reports show year-over-year values.
Users report that the performance of some of the reports has degraded over time and some visuals show errors.
You need to resolve the performance issues. The solution must meet the following requirements:
Provide the best query performance.
Minimize operational costs.
Which should you do?
- A. Create views.
- B. Change the MD5 hash to SHA256.
- C. Modify the surrogate keys to use a different data type.
- D. Increase the capacity.C Enable V-Order
Answer: C
Explanation:
In this case, the key issue causing performance degradation likely stems from the use of MD5 hash surrogate keys. MD5 hashes are 128-bit values, which can be inefficient for large datasets like the 500 million rows in your fact table. Using a more efficient data type for surrogate keys (such as integer or bigint) would reduce the storage and processing overhead, leading to better query performance. This approach will improve performance while minimizing operational costs because it reduces the complexity of querying and indexing, as smaller data types are generally faster and more efficient to process.
NEW QUESTION # 119
HOTSPOT
You have a Fabric workspace that contains two lakehouses named Lakehouse1 and Lakehouse2. Lakehouse1 contains staging data in a Delta table named Orderlines. Lakehouse2 contains a Type 2 slowly changing dimension (SCD) dimension table named Dim_Customer.
You need to build a query that will combine data from Orderlines and Dim_Customer to create a new fact table named Fact_Orders. The new table must meet the following requirements:
Enable the analysis of customer orders based on historical attributes.
Enable the analysis of customer orders based on the current attributes.
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 # 120
You need to ensure that the data engineers are notified if any step in populating the lakehouses fails. The solution must meet the technical requirements and minimize development effort.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

NEW QUESTION # 121
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