VALID DP-700 TEST NOTES & DP-700 INSTANT ACCESS

Valid DP-700 Test Notes & DP-700 Instant Access

Valid DP-700 Test Notes & DP-700 Instant Access

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Tags: Valid DP-700 Test Notes, DP-700 Instant Access, DP-700 Detailed Study Plan, DP-700 Valid Test Braindumps, DP-700 Latest Real Test

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Microsoft DP-700 Instant Access & DP-700 Detailed Study Plan

The Microsoft DP-700 exam questions are the ideal and recommended study material for quick and easiest Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam dumps preparation. The Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) practice questions are designed and verified by qualified and renowned Microsoft Certification Exams trainers. They work closely and check all DP-700 Exam Dumps step by step. They also ensure the best possible answer for all DP-700 exam questions and strive hard to maintain the top standard of Implementing Data Engineering Solutions Using Microsoft Fabric (DP-700) exam dumps all the time.

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q30-Q35):

NEW QUESTION # 30
You have a Fabric workspace that contains a takehouse and a semantic model named Model1.
You use a notebook named Notebook1 to ingest and transform data from an external data source.
You need to execute Notebook1 as part of a data pipeline named Pipeline1. The process must meet the following requirements:
* Run daily at 07:00 AM UTC.
* Attempt to retry Notebook1 twice if the notebook fails.
* After Notebook1 executes successfully, refresh Model1.
Which three actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

  • A. From the Schedule settings of Notebook1, set the time zone to UTC.
  • B. From the Schedule settings of Pipeline1, set the time zone to UTC.
  • C. Set the Retry setting of the Notebook activity to 2.
  • D. Set the Retry setting of the Semantic model refresh activity to 2.
  • E. Place the Semantic model refresh activity after the Notebook activity and link the activities by using an On completion condition.
  • F. Place the Semantic model refresh activity after the Notebook activity and link the activities by using the On success condition.

Answer: B,C,F


NEW QUESTION # 31
You have a Fabric workspace.
You have semi-structured data.
You need to read the data by using T-SQL, KQL, and Apache Spark. The data will only be written by using Spark.
What should you use to store the data?

  • A. a warehouse
  • B. a datamart
  • C. an eventhouse
  • D. a lakehouse

Answer: D

Explanation:
A lakehouse is the best option for storing semi-structured data when you need to read it using T-SQL, KQL, and Apache Spark. A lakehouse combines the flexibility of a data lake (which can handle semi-structured and unstructured data) with the performance features of a data warehouse. It allows data to be written using Apache Spark and can be queried using different technologies such as T-SQL (for SQL-based querying), KQL (Kusto Query Language for querying), and Apache Spark (for distributed processing). This solution is ideal when dealing with semi-structured data and requiring a versatile querying approach.


NEW QUESTION # 32
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:


NEW QUESTION # 33
You have a Fabric workspace that contains a lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Table1.
You analyze Table1 and discover that Table1 contains 2,000 Parquet files of 1 MB each.
You need to minimize how long it takes to query Table1.
What should you do?

  • A. Disable V-Order and run the OPTIMIZE command.
  • B. Run the OPTIMIZE and VACUUM commands.
  • C. Disable V-Order and run the VACUUM command.

Answer: B

Explanation:
Problem Overview:
Solution:
Commands and Their Roles:
- Compacts small Parquet files into larger files to improve query performance.
- It supports optional features like V-Order, which organizes data for efficient scanning.
- Removes old, unreferenced data files and metadata from the Delta table.
- Running VACUUM after OPTIMIZE ensures unnecessary files are cleaned up, reducing storage overhead and improving performance.


NEW QUESTION # 34
You have an Azure key vault named KeyVaultl that contains secrets.
You have a Fabric workspace named Workspace-!. Workspace! contains a notebook named Notebookl that performs the following tasks:
* Loads stage data to the target tables in a lakehouse
* Triggers the refresh of a semantic model
You plan to add functionality to Notebookl that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVaultl to generate the authentication token.
Solution: You use the following code segment:
Use notebookutils.credentials.getSecret and specify the key vault URL and key vault secret. Does this meet the goal?

  • A. No
  • B. Yes

Answer: B


NEW QUESTION # 35
......

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