DP-600 practice questions 101–110

1. Question 101 · 190 in bank

   HOTSPOT - You have a Fabric tenant that contains two lakehouses. You are building a dataflow that will combine data from the lakehouses. The applied steps from one of the queries in the dataflow is shown in the following exhibit.

   

   Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   1: Some.blue icone fold and red dont fold 2 : on power query. all process after the step that dont fold are on power query

   Source: Adapted from community discussion — Momoanwar

   References

   • Microsoft Learn

   

   Next question

2. Question 102 · 190 in bank

   You have a Fabric tenant that contains a lakehouse named Lakehouse’. Lakehouse1 contains a table named Tablet. You are creating a new data pipeline. You plan to copy external data to Table’. The schema of the external data changes regularly. You need the copy operation to meet the following requirements: Replace Table1 with the schema of the external data. Replace all the data in Table1 with the rows in the external data. You add a Copy data activity to the pipeline. What should you do for the Copy data activity?

   • AFrom the Source tab, add additional columns.
   • BFrom the Destination tab, set Table action to Overwrite.
   • CFrom the Settings tab, select Enable staging.
   • DFrom the Source tab, select Enable partition discovery.
   • EFrom the Source tab, select Recursively.

   Show answer

   Answer: B

   Explanation

   Correct: Enable "Truncate table" option: This option truncates the target table before copying data, ensuring that all existing data is replaced with the new data from the external source.

   Source: Adapted from community discussion — IshtarSQL

   References

   • Microsoft Learn

   Next question

3. Question 103 · 190 in bank

   Select 2

   You have a Fabric tenant that contains a lakehouse. You plan to query sales data files by using the SQL endpoint. The files will be in an Amazon Simple Storage Service (Amazon S3) storage bucket. You need to recommend which file format to use and where to create a shortcut. Which two actions should you include in the recommendation? Each correct answer presents part of the solution. NOTE: Each correct answer is worth one point.

   • ACreate a shortcut in the Files section.
   • BUse the Parquet format
   • CUse the CSV format.
   • DCreate a shortcut in the Tables section.
   • EUse the delta format.

   Show answer

   Answer: BD

   Explanation

   Answer is DE. To be able to use the SQL Endpoint you need to create the shortcut in the Tables section. The file also needs to be in the delta format to be recognised as a managed table. If you try to add a parquet file to the tables section, it will not be recognised as a table object and you won't be able to query it.

   Source: Adapted from community discussion — Felgas

   References

   • Microsoft Learn
   • Microsoft Learn
   • AWS documentation
   • Microsoft Learn
   • Microsoft Learn

   Next question

4. Question 104 · 190 in bank

   You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a subfolder named Subfolder1 that contains CSV files. You need to convert the CSV files into the delta format that has V-Order optimization enabled. What should you do from Lakehouse explorer?

   • AUse the Load to Tables feature.
   • BCreate a new shortcut in the Files section.
   • CCreate a new shortcut in the Tables section.
   • DUse the Optimize feature.

   Show answer

   Answer: A

   Explanation

   With ''Load to tables'' : tables are always loaded using the Delta Lake table format with V-Order optimization enabled. https://learn.microsoft.com/en-us/fabric/data-engineering/load-to-tables#load-to-table-capabilities-overview

   Source: Adapted from community discussion — Sanji931

   References

   • Microsoft Learn
   • Microsoft Learn

   Next question

5. Question 105 · 190 in bank

   You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains an unpartitioned table named Table1. You plan to copy data to Table1 and partition the table based on a date column in the source data. You create a Copy activity to copy the data to Table1. You need to specify the partition column in the Destination settings of the Copy activity. What should you do first?

   • AFrom the Destination tab, set Mode to Append.
   • BFrom the Destination tab, select the partition column.
   • CFrom the Source tab, select Enable partition discovery.
   • DFrom the Destination tabs, set Mode to Overwrite.

   Show answer

   Answer: D

   Explanation

   D. From the Destination tabs, set Mode to Overwrite. When setting up the Copy Activity, you need to choose the Overwrite mode to make the partition option appear (not visibile in Append mode).

   Source: Adapted from community discussion — SamuComqi

   References

   • Microsoft Learn
   • Microsoft Learn

   Next question

6. Question 106 · 190 in bank

   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?

   • Aspark.read.format(“delta”).load(“Tables/productline1/ResearchProduct”)
   • Bspark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”)
   • Cexternal_table(‘Tables/ResearchProduct)
   • Dexternal_table(ResearchProduct)

   Show answer

   Answer: B

   Explanation

   B. spark.sql(“SELECT * FROM Lakehouse1.ResearchProduct ”) The syntax of C and D is correct for KQL databases (incorrect in this use-case). When the shortcut is created, no additional folders have been added to the Tables section, therefore answer A is incorrect. Once created, the line of answer B can be used to access data correctly. https://learn.microsoft.com/en-us/fabric/onelake/onelake-shortcuts

   Source: Adapted from community discussion — SamuComqi

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   Next question

7. Question 107 · 190 in bank

   You have source data in a folder on a local computer. You need to create a solution that will use Fabric to populate a data store. The solution must meet the following requirements: Support the use of dataflows to load and append data to the data store. Ensure that Delta tables are V-Order optimized and compacted automatically. Which type of data store should you use?

   • Aa lakehouse
   • Ban Azure SQL database
   • Ca warehouse
   • Da KQL database

   Show answer

   Answer: A

   Explanation

   I have recently taken the exam and this question was asked.Its a multiple choice question.we need to select 2 options.so as per the comments both lakehouse and warehouse are support delta tables and v-order optimization.Its A,C

   Source: Adapted from community discussion — bvmony2294

   References

   • Microsoft Learn
   • Microsoft Learn

   Next question

8. Question 108 · 190 in bank

   HOTSPOT - You have a Fabric tenant that contains a lakehouse. You are using a Fabric notebook to save a large DataFrame by using the following code. df.write.partitionBy(“year”, “month”, “day”).mode(“overwrite”).parquet(“Files/SalesOrder”) For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Y-Y-N The results will form a hierarchy of folders for each partition key: Yes: When using partitionBy in Spark, the data is organized into a hierarchical directory structure based on the specified partition keys. Therefore, you will see directories like year=YYYY/month=MM/day=DD within the specified output path. The resulting file partitions can be read in parallel across multiple nodes: Yes: Parquet files are designed for efficient querying and support parallel processing. Spark can read these partitions in parallel, enabling distributed query execution across multiple nodes. The resulting file partitions will use file compression: No: While Parquet format supports compression, it is not enabled by default in the code snippet provided. Compression needs to be explicitly specified if required. For example, you could use .option("compression", "snappy") to enable Snappy compression.

   Source: Adapted from community discussion — 282b85d

   

   Next question

9. Question 109 · 190 in bank

   You have a Fabric workspace named Workspace1 that contains a data flow named Dataflow1 contains a query that returns the data shown in the following exhibit.

   

   You need to transform the data columns into attribute-value pairs, where columns become rows. You select the VendorID column. Which transformation should you select from the context menu of the VendorID column?

   • AGroup by
   • BUnpivot columns
   • CUnpivot other columns
   • DSplit column
   • ERemove other columns

   Show answer

   Answer: C

   Explanation

   IMHO, "C", Because of: Unpivot other columns This command unpivots unselected columns. Use this command in a query when not all columns are known. New columns added during a refresh operation are also unpivoted. description is here: https://support.microsoft.com/en-us/office/unpivot-columns-power-query-0f7bad4b-9ea1-49c1-9d95-f588221c7098#:~:text=Select%20the%20columns%20you%20do,Transform%20%3E%20Unpivot%20Only%20Selected%20Columns.

   Source: Adapted from community discussion — stilferx

   Next question

10. Question 110 · 190 in bank

    You have a Fabric tenant that contains a data pipeline. You need to ensure that the pipeline runs every four hours on Mondays and Fridays. To what should you set Repeat for the schedule?

    • ADaily
    • BBy the minute
    • CWeekly
    • DHourly

    Show answer

    Answer: C

    Explanation

    Answer C : Weekly. The only way to do this is to set the schedule to ''Weekly'', set the days on Monday and Friday and add manually 6 Time of 4 hour intervals.

    Source: Adapted from community discussion — Sanji931

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

DP-600 practice, question 101. 190 questions available.