exam questions

Exam DP-600 All Questions

View all questions & answers for the DP-600 exam

Exam DP-600 topic 1 question 4 discussion

Actual exam question from Microsoft's DP-600
Question #: 4
Topic #: 1
[All DP-600 Questions]

Case study -
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -
Contoso, Ltd. is a US-based health supplements company. Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.

Existing Environment -

Identity Environment -
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroup1 and ResearchReviewersGroup2.

Data Environment -
Contoso has the following data environment:
The Sales division uses a Microsoft Power BI Premium capacity.
The semantic model of the Online Sales department includes a fact table named Orders that uses Import made. In the system of origin, the OrderID value represents the sequence in which orders are created.
The Research department uses an on-premises, third-party data warehousing product.
Fabric is enabled for contoso.com.
An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Productline1. The data is in the delta format.
A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.

Requirements -

Planned Changes -
Contoso plans to make the following changes:
Enable support for Fabric in the Power BI Premium capacity used by the Sales division.
Make all the data for the Sales division and the Research division available in Fabric.
For the Research division, create two Fabric workspaces named Productline1ws and Productine2ws.
In Productline1ws, create a lakehouse named Lakehouse1.
In Lakehouse1, create a shortcut to storage1 named ResearchProduct.

Data Analytics Requirements -
Contoso identifies the following data analytics requirements:
All the workspaces for the Sales division and the Research division must support all Fabric experiences.
The Research division workspaces must use a dedicated, on-demand capacity that has per-minute billing.
The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.
For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.
All the semantic models and reports for the Research division must use version control that supports branching.

Data Preparation Requirements -
Contoso identifies the following data preparation requirements:
The Research division data for Productline1 must be retrieved from Lakehouse1 by using Fabric notebooks.
All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.

Semantic Model Requirements -
Contoso identifies the following requirements for implementing and managing semantic models:
The number of rows added to the Orders table during refreshes must be minimized.
The semantic models in the Research division workspaces must use Direct Lake mode.

General Requirements -
Contoso identifies the following high-level requirements that must be considered for all solutions:
Follow the principle of least privilege when applicable.
Minimize implementation and maintenance effort when possible.
Which syntax should you use in a notebook to access the Research division data for Productline1?

  • A. spark.read.format(“delta”).load(“Tables/productline1/ResearchProduct”)
  • B. spark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”)
  • C. external_table(‘Tables/ResearchProduct)
  • D. external_table(ResearchProduct)
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
David_Webb
Highly Voted 1 year, 2 months ago
Selected Answer: B
The correct answer is B. The folder hierarchy of Tables in Lakehouse is incorrect for A.
upvoted 15 times
a998450
1 year ago
Yes B is correct answer as per the requirement specified in case study - For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
upvoted 6 times
...
...
wispa2001
Highly Voted 7 months ago
Selected Answer: B
df = spark.read.format("delta").load("Tables/MyShortcut") display(df) OR df = spark.sql("SELECT * FROM MyLakehouse.MyShortcut LIMIT 1000") display(df) https://learn.microsoft.com/en-us/fabric/onelake/onelake-shortcuts
upvoted 10 times
...
Atiwari95
Most Recent 4 weeks ago
Selected Answer: B
The Correct Answer is B. The hierarchy of table is correct in B option.
upvoted 1 times
...
NRezgui
4 months ago
Selected Answer: B
spark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”)
upvoted 1 times
...
NRezgui
4 months ago
Selected Answer: B
spark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”)
upvoted 1 times
...
MultiCloudIronMan
4 months, 2 weeks ago
Selected Answer: A
Based on the case study details, the data for Productline1 is stored in an Azure Data Lake Storage Gen2 storage account named storage1 in the delta format. A shortcut to this storage, named ResearchProduct, is created in Lakehouse1 within the Productline1ws workspace. Given this structure, the path "Tables/productline1/ResearchProduct" is justified because it references the shortcut created in Lakehouse1 that points to the data stored in storage1. This path aligns with the case study's description of the data environment and planned changes.
upvoted 2 times
Chandler9714
1 month, 2 weeks ago
"In Lakehouse1, create a shortcut to storage1 named ResearchProduct." The shortcut is to storage 1 not productline1. If the shortcut was specific to productline1 and placed in the folder, I think this would then be correct, but thats not the case here.
upvoted 1 times
...
...
Rakesh16
5 months, 1 week ago
Selected Answer: B
B-->spark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”)
upvoted 1 times
...
jass007_k
6 months ago
The correct answer is B) Though A also looks correct, but the path mentioned is incorrect. The path should be Tables/ResearchProduct. We are directly creating a shortcut with the name ResearchProduct under Tables folder in Lakehouse1. There is no mention of the productline1 folder created.
upvoted 3 times
...
jass007_k
6 months ago
Both seem to be correct option A and option B. I have tried both syntaxes with shortcut data. Also its mentioned that format of data is in delta so I will go with option A)
upvoted 2 times
...
Egocentric
6 months, 1 week ago
A is for when you want to load data. Answer is B, its only when you requesting specific data from specific table
upvoted 3 times
...
Egocentric
8 months ago
answer is A. in B there is no productline1
upvoted 2 times
...
nyoike
8 months, 3 weeks ago
Selected Answer: A
With the recent introduction of schema-enabled Lakehouses, BOTH A and B are correct. That is assuming ResearchProduct table was created in a schema-enabled Lakehouse in the productline1 schema. I have tested A in a Fabric Spark notebook that is schema-enabled and it works.
upvoted 6 times
...
Miro_dd
9 months, 4 weeks ago
Selected Answer: B
Hierarchy for answer A is not correct
upvoted 1 times
...
ziggy1117
10 months, 1 week ago
Selected Answer: B
https://learn.microsoft.com/en-us/fabric/onelake/onelake-shortcuts df = spark.read.format("delta").load("Tables/MyShortcut") OR df = spark.sql("SELECT * FROM MyLakehouse.MyShortcut LIMIT 1000")
upvoted 1 times
...
ca63a55
11 months, 1 week ago
If answer B is the correct, why Files folder dosen`t appear between Lakehouse1 and ResearchProduct? It has to be like "lakehouse1.Files.ResearchProduct", hasn't it?
upvoted 1 times
...
stilferx
11 months, 3 weeks ago
Selected Answer: A
IMHO, I would go with A, because of there is a clear statement ProductLine1. Technically, A and B should work, but B doesn't have "ProductLine", what is confusing
upvoted 1 times
stilferx
11 months, 2 weeks ago
My bad, the right answer is B. There is a requirement: Research Division - all tables should be managed. It means, no subfolders should be. https://learn.microsoft.com/en-us/training/modules/use-apache-spark-work-files-lakehouse/5-spark-sql
upvoted 5 times
...
...
KASH2001
11 months, 3 weeks ago
There is no productline1 used in Answer B. Then how it could be correct....
upvoted 1 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
Loading ...
exam
Someone Bought Contributor Access for:
SY0-701
London, 1 minute ago