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Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
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.
Topic 2
  • 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.
Topic 3
  • 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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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q14-Q19):

NEW QUESTION # 14
You have five Fabric workspaces.
You are monitoring the execution of items by using Monitoring hub.
You need to identify in which workspace a specific item runs.
Which column should you view in Monitoring hub?

Answer: E

Explanation:
To identify in which workspace a specific item runs in Monitoring hub, you should view the Location column. This column indicates the workspace where the item is executed. Since you have multiple workspaces and need to track the execution of items across them, the Location column will show you the exact workspace associated with each item or job execution.


NEW QUESTION # 15
You have a Fabric workspace named Workspace1 that uses version control. Workspace! and Azure DevOps are integrated.
In Azure DevOps. developers create a branch named Branch1 to test extract, transform, and load (ETL) updates.
You need to connect Workspace1 to Branch1. The solution must ensure that all the existing content in Branch1 is available in Workspace1.
What should you do?

Answer: C


NEW QUESTION # 16
You have a Fabric workspace.
You plan to deploy two Apache Spark environments that will each contain one of the following notebooks:
* Notebook 1: A data ingestion notebook that will run as a scheduled Spark job
* Notebook2; An ad hoc notebook for interactive data analysis that will be used by a team of analysts and data scientists You need to configure the Spark environments to meet the following requirements:
* For the environment that contains Notebook 1, minimize compute costs.
* For the environment that contains Notebook2, support multiple concurrent users.
What should you use for each environment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 17
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?

Answer: D

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 # 18
You have a Fabric data warehouse that contains the following tables.

You need to refresh the tables by using an automated pipeline. The solution must ensure that table updates occur in the correct order to maintain referential integrity.
Which two tables should you refresh first? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: A,B


NEW QUESTION # 19
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