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Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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 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 (Q133-Q138):

NEW QUESTION # 133
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 # 134
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse2. A team of data analysts has Viewer role access to Workspace1. You create a table by running the following statement.

You need to ensure that the team can view only the first two characters and the last four characters of the Creditcard attribute.
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 # 135
HOTSPOT
You are building a data loading pattern for Fabric notebook workloads.
You have the following code segment:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 136
You have a Fabric workspace named Workspace1.
You enable workspace monitoring for Workspace1.
You need to return records ingested during the last 540 seconds.
Which KQL filter should you use?

Answer: A

Explanation:
The correct answer is C because the requirement is specifically to identify records based on when they were ingested into the Fabric monitoring data store , rather than when a monitored job started or ended.
In KQL, ingestion_time() returns the approximate UTC datetime at which the current record was ingested and became available for querying. The datetime_diff() function uses the syntax datetime_diff(period, datetime1, datetime2) and effectively calculates the difference between datetime1 and datetime2. Therefore:
datetime_diff( ' second ' , now(), ingestion_time())
calculates how many seconds have elapsed between the record ' s ingestion time and the current time.
Filtering for values < = 540 returns records ingested within approximately the previous nine minutes.
Microsoft explicitly uses this same expression in Fabric workspace-monitoring examples for retrieving recent records. ( Microsoft Learn ) Options A and B evaluate job execution timestamps rather than ingestion recency. Option D reverses the datetime operands, which normally produces a negative elapsed-time value and therefore does not correctly represent " seconds ago. " Study Guide reference: Monitor and optimize an analytics solution # monitor Fabric workloads, workspace monitoring, KQL querying, and operational log analysis. ( Microsoft Learn )


NEW QUESTION # 137
HOTSPOT
You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains the following tables and columns.

You need to denormalize the tables and include the ContractType and StartDate columns in the Employee table. The solution must meet the following requirements:
Ensure that the StartDate column is of the date data type.
Ensure that all the rows from the Employee table are preserved and include any matching rows from the Contract table.
Ensure that the result set displays the total number of employees per contract type for all the contract types that have more than two employees.
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 # 138
......

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