Microsoft DP-750 Exam Questions

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Microsoft DP-750 Sample Questions

Question # 1

You have an Azure Databricks workspace that is enabled for Unity CatalogYou have a complex job named Job1 that contains eight tasks. Job! takes multiple hours tocompleteDuring the last job run, the final task fails due to a transient issue.You need to retry the last task without rerunning tasks that have already completed.What should you do?

A. Update the job parameters.
B. Repair the current job run.
C. Restart Job!
D. Disable and reenable the job schedule

Show Answer

Question # 2

You have an Azure Databricks workspace that is enabled for Unity Catalog.You need to recommend a pipeline that ingests files from cloud storage, performscleansing and enrichment transformations, and writes created Delta tables for analytics.The solution must minimize development effort and provide built-in monitoring andautomatic retries.What should you include in the recommendation?

A. an Apache Spark Structured Streaming job 
B. a Databricks notebook triggered by a scheduled job
C. a Lakeflow Spark Declarative Pipelines (SDPJ pipeline
D. an Azure Data Factory pipeline that uses data flows

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Question # 3

You have an Azure Databricks workspace that is enabled for Unity Catalog and contains acatalog named Catalog 1. Catalog 1 contains a table named Transactions. Transactionscontains the following columns:• transaction_id• customet_name• email address• credit_card_number• transaction_amountYou need to ensure that business analysts can query all the tows in the Transactions table.The solution must meet the following requirements:• Prevent the analysts from seeing the full values in the email_address andcredit_catd_number columns.• Ensure that the analysts can see only the values after the @ character in each emailaddress.• Ensure that the analysts can see only the last four digits of each credit card number.• Enable the analysts to query the table without errors.• Follow the principle of least privilege.What should you do?

A. Grant the analysts the SELECT permission for the Transactions table and implement row-level filters.
B. Grant the analysts the select permission for columns that do NOT contain sensitive data. 
C. Grant the analysts the select permission for the Transactions table and apply column masks to email_address and credit_card_number
D. Grant the analysts the select permission for the Transactions table and apply columnlevel encryption 

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Question # 4

You have an Azure Databricks workspace that is enabled for Unity Catalog and contains aDelta table named Sales_orders. Sales.orders stores historical sales data.You receive a daily CSV file daily that contains new sales records only. The file does NOTcontain updates to existing rows You need to load the daily data into Sales.orders. Thesolution must meet the following requirements:• Preserve the existing data.• Add only the new records.• Minimize processing effort.Which command should include in the loading strategy?

A. INSERT OVERWRITE
B. UPDATE
C. INSERT INTO

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Question # 5

You have an Azure Databricks workspace that is enabled for Unity Catalog and contains amanaged Delta table named Table1. Table1 stores customer data.You need to implement a data retention solution that meets the following requirements:Deleted data must be retained for 30 days to support audits.Deleted data that is older than 30 days must be removed permanently.The solution must minimize administrative effort.Which two properties should you configure? Each correct answer presents part of thesolution.NOTE: Each correct selection is worth one point.

A. delta.timeUntilArchived
B. delta.deletedFileRetentionDuration
C. delta.autoOptimize.autoCompact
D. delta.logRetentionDuration
E. delta.enableDeletionVectors

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Question # 6

You have an Azure Databricks workspace named Workspace! that uses a Git repository.The repository contains a Databricks notebook named Notebook1.From the main branch, you create a feature branch named Branch! and commit changes toNotebooks Another user commits changes to Notebook1 in main.When you attempt to merge Branch! into main, the merge fails due to conflicts.You need to merge Branch! into the main branch. The solution must ensure that Notebook1includes all the changes from both the branches.What should you do?

A. From Workspace1, clone Branch! as a new repository.
B. Apply the changes directly to the main branch.
C. From Workspace1, clone the mam branch as a new repository.
D. Apply the main branch changes to Branch! and resolve the conflicts.

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Question # 7

You have an Azure Databricks workspace named Workspace1 that contains a takehouseand is enabled for Unity Catalog.You have a connection to a Microsoft SQL Server database named DB1.You need to expose the schemas and tables of DB1 to meet the following requirements:• The schemas and tables can be queried in Databricks.• The schemas and tables appear alongside other Unity Catalog objects.• The data is NOT copied into Databricks-managed storage.Solution: You create a new native catalog in Unity Catalog. Does this meet the goal?

A. Yes
B. No

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Question # 8

You need to deploy Databricks Asset Bundles to a development environment. The solution must support automated and repeatable deployments across environments. What should you use? 

A. the Azure Developer CLI (azd)
B. Git folders
C. the Databricks CLI
D. the Azure Command-Line Interface (CLI)

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Question # 9

You have an Azure Databricks workspace that uses Unity Catalog.You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that ingests data into amanaged Delta table named Table1. Table! is used for analytics.New columns are added to the source data, causing pipeline failures during writes to Table!You need to prevent the pipeline failures. The solution must ensure that schema changesare detected and handled.What should you do?

A. Disable schema enforcement for Table1.
B. Use row filters to exclude records that have new columns.
C. Enable schema evolution.
D. Create a separate table for each schema version.

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Question # 10

You have an Azure Databricks workspace named Workspace1 that contains a lakehouseand is enabled for Unity Catalog.You have a connection to a Microsoft SQL Server database named DB1.You need to expose the schemas and tables of DB1 to meet the following requirements:• The schemas and tables can be queried in Databricks.• The schemas and tables appear alongside other Unity Catalog objects.• The data is NOT copied into Databricks-managed storage.Solution: You create a Lakeflow Connect pipeline and connect it to DB1. Does this meetthe goal?

A. Yes
B. No

Show Answer

Question # 11

You have an Azure Databricks workspace that is enabled for Unity CatalogYou have an Apache Spark Structured Streaming job that writes data to a Delta table.After the cluster restarts, the streaming job reprocesses previously ingested dataYou need to prevent the streaming job from reprocessing the data after the cluster restarts.What should you do?

A. Increase the trigger interval of the streaming query.
B. Configure a checkpoint location for the streaming query.
C. Configure a watermark for the streaming query.
D. Enable change data feed (CDF) for the target table.

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Question # 12

You have an Azure Databricks workspace that is enabled for Unity Catalog and containstwo managed Delta tables named sales.schema1.table1 and sales.schema1.table2.sales.schema1.table1 contains sales data from the current year.sales.schema1.table2 contains historical data.You need to load all the rows from sales.schema1.table1 into sales.schema1.table2. Thesolution must preserve any existing data in sales.schema1.table2 and minimize processingeffort.Which command should you run?

A. INSERT INTO sales.schema1.table2 SELECT * FROM sales.schema1.table1; 
B. CREATE TABLE sales.schema1.table2 AS SELECT * FROM sales.schema1.table1;
C. INSERT OVERWRITE sales.schema1.table2 SELECT * FROM sales.schema1.table1;
D. CREATE OR REPLACE TABLE sales.schema1.table2 AS SELECT * FROMsales.schema1.table1

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Question # 13

You have an Azure Databricks workspace that is enabled for Unity Catalog and contains aDelta table named Orders.You load the Orders table into an Apache Spark DataFrame named df.You need to create a DataFrame that excludes rows where the order amount is null.Solution: You run the following expression.df.filter(df.order_amount != None)Does this meet the goal?

A. Yes
B. No

Show Answer