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DP-700 Implementing Data Engineering Solutions Using Microsoft Fabric

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Microsoft · DP-700

Free DP-700 Exam Dumps Preview

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Question 1

Single choice

You have two Fabric workspaces named Workspace1 and Workspace2.

You have a Fabric deployment pipeline named deploy Pipeline1 that deploys items from Workspace1 to Workspace2.

DeployPipeline1 contains all the items in Workspace1.

You recently modified the items in Workspaces1.

The workspaces currently contain the items shown in the following table.

Items in Workspace1 that have the same name as items in Workspace2 are currently paired.

You need to ensure that the items in Workspace1 overwrite the corresponding items in Workspace2. The solution must minimize effort.

What should you do?

A
Delete all the items in Workspace2, and then run deployPipeline1.
B
Rename each item in Workspace2 to have the same name as the items in Workspace1.
C
Back up the items in Workspace2, and then run deployPipeline1.
D
Run deployPipeline1 without modifying the items in Workspace2.

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Correct answerD

Question 2

Hotspot

HOTSPOT

You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains a table named DimCustomers. DimCustomers contains the following columns:

1. CustomerName
2. CustomerID
3. BirthDate
4. EmailAddress

You need to configure security to meet the following requirements:

1. BirthDate in DimCustomer must be masked and display 1900-01-01.
2. EmailAddress in DimCustomer must be masked and display only the first leading character and the last five characters.

How should you complete the statement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Question 3

Single choice

You need to automatically trigger a pipeline when new CSV files land in Azure Data Lake Storage.

Which trigger type should you use?

A
Manual
B
Schedule
C
Storage event trigger
D
Custom event trigger

Reveal answer details Close answer details

Correct answerC

Question 4

Hotspot

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 Type2 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:

1. Enable the analysis of customer orders based on historical attributes.
2. 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.

stem image

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Question 5

Single choice

You need to build a Power Apps application that connects to a customer's existing SQL Server database.

The database contains sensitive information, and security is a primary requirement.

Which Power Apps capability should be used to provide secure access to this data?

A
Environment Variables
B
Role-Based Security
C
Custom Connectors
D
On-Premises Data Gateway

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Correct answerD

Question 6

Hotspot

HOTSPOT

You have the development groups shown in the following table.

You have the projects shown in the following table.

You need to recommend which Fabric item to use based on each development group's skillset. The solution must meet the project requirements and minimize development effort.

What should you recommend for each group? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Explanation

Box 1: An eventstream
Group1: Azure Stream Analytics with Azure Event hubs Project1: Move data between source and sink environments

With Azure Event Hubs and Azure Stream Analytics, the Microsoft Fabric solution that can move data between source and sink environments is Fabric eventstreams, which allows you to bring real-time events into Fabric, transform them, and route them to various Fabric destinations without writing code.

Box 2: A Dataflow Gen2
Group2: Microsoft Power BI
Project2: Transform data by using a low-code approach.

For Microsoft Power BI, the Fabric solution for low-code data transformation is Dataflows Gen2, which provides the familiar, visual, and low-code Power Query experience for ingesting and transforming data from various sources before it's loaded into OneLake and made available for Power BI and other workloads.

Box 3: A notebook
Group3: R language
Project3: Transform data

Use notebooks for data preparation, data visualization, machine learning, and other big data scenarios. To get started with R in Microsoft Fabric notebooks, change the primary language at the top of your notebook to SparkR (R).

References:
https://learn.microsoft.com/en-us/fabric/real-time-intelligence/event-streams/overview
https://learn.microsoft.com/en-us/fabric/data-factory/decision-guide-data-integration
https://learn.microsoft.com/en-us/fabric/data-science/r-overview

Question 7

Single choice

You have a Fabric workspace that contains a lakehouse named Lakehouse1.

In an external data source, you have data files that are 500 GB each. A new file is added every day.

You need to ingest the data into Lakehouse1 without applying any transformations.

The solution must meet the following requirements:

1. Trigger the process when a new file is added.
2. Provide the highest throughput.

Which type of item should you use to ingest the data?

A
Data pipeline
B
Eventstream
C
Streaming dataset
D
Dataflow Gen2

Reveal answer details Close answer details

Correct answerA

Case study

Case Study 1

Overview. Company Overview
Contoso, Ltd. is an online retail company that wants to modernize its analytics platform by moving to Fabric.
The company plans to begin using Fabric for marketing analytics.

Overview. IT Structure
The company's IT department has a team of data analysts and a team of data engineers that use analytics systems.
The data engineers perform the ingestion, transformation, and loading of data. They prefer to use Python or SQL to transform the data.
The data analysts query data and create semantic models and reports. They are qualified to write queries in Power Query and T-SQL.

Existing Environment. Fabric
Contoso has an F64 capacity named Cap1. All Fabric users are allowed to create items. Contoso has two workspaces named WorkspaceA and WorkspaceB that currently use Pro license mode. Existing Environment. Source Systems Contoso has a point of sale (POS) system named POS1 that uses an instance of SQL Server on Azure Virtual Machines in the same Microsoft Entra tenant as Fabric. The host virtual machine is on a private virtual network that has public access blocked. POS1 contains all the sales transactions that were processed on the company's website.

The company has a software as a service (SaaS) online marketing app named MAR1. MAR1 has seven entities. The entities contain data that relates to email open rates and interaction rates, as well as website interactions. The data can be exported from MAR1 by calling REST APIs. Each entity has a different endpoint.

Contoso has been using MAR1 for one year. Data from prior years is stored in Parquet files in an Amazon Simple Storage Service (Amazon S3) bucket. There are 12 files that range in size from 300 MB to 900 MB and relate to email interactions.

Existing Environment. Product Data
POS1 contains a product list and related data. The data comes from the following three tables:

Products
ProductCategories

ProductSubcategories

In the data, products are related to product subcategories, and subcategories are related to product categories.

Existing Environment. Azure
Contoso has a Microsoft Entra tenant that has the following mail-enabled security groups: DataAnalysts: Contains the data analysts DataEngineers: Contains the data engineers

Contoso has an Azure subscription.
The company has an existing Azure DevOps organization and creates a new project for repositories that relate to Fabric. Existing Environment. User Problems The VP of marketing at Contoso requires analysis on the effectiveness of different types of email content. It typically takes a week to manually compile and analyze the data. Contoso wants to reduce the time to less than one day by using Fabric.

The data engineering team has successfully exported data from MAR1. The team experiences transient connectivity errors, which causes the data exports to fail.

Requirements. Planned Changes

Contoso plans to create the following two lakehouses: Lakehouse1: Will store both raw and cleansed data from the sources Lakehouse2: Will serve data in a dimensional model to users for analytical queries Additional items will be added to facilitate data ingestion and transformation.
Contoso plans to use Azure Repos for source control in Fabric.

Requirements. Technical Requirements
The new lakehouses must follow a medallion architecture by using the following three layers: bronze, silver, and gold. There will be extensive data cleansing required to populate the MAR1 data in the silver layer, including deduplication, the handling of missing values, and the standardizing of capitalization.

Each layer must be fully populated before moving on to the next layer. If any step in populating the lakehouses fails, an email must be sent to the data engineers.

Data imports must run simultaneously, when possible.
The use of email data from the Amazon S3 bucket must meet the following requirements: Minimize egress costs associated with cross-cloud data access.
Prevent saving a copy of the raw data in the lakehouses.

Items that relate to data ingestion must meet the following requirements: The items must be source controlled alongside other workspace items.
Ingested data must land in the bronze layer of Lakehouse1 in the Delta format.

No changes other than changes to the file formats must be implemented before the data lands in the bronze layer.

Development effort must be minimized and a built-in connection must be used to import the source data.

In the event of a connectivity error, the ingestion processes must attempt the connection again.

Lakehouses, data pipelines, and notebooks must be stored in WorkspaceA. Semantic models, reports, and dataflows must be stored in WorkspaceB.

Once a week, old files that are no longer referenced by a Delta table log must be removed.

Requirements. Data Transformation

In the POS1 product data, ProductID values are unique. The product dimension in the gold layer must include only active products from product list. Active products are identified by an IsActive value of 1.

Some product categories and subcategories are NOT assigned to any product. They are NOT analytically relevant and must be omitted from the product dimension in the gold layer.

Requirements. Data Security

Security in Fabric must meet the following requirements:
1. The data engineers must have read and write access to all the lakehouses, including the underlying files.
2. The data analysts must only have read access to the Delta tables in the gold layer.
3. The data analysts must NOT have access to the data in the bronze and silver layers.
4. The data engineers must be able to commit changes to source control in WorkspaceA.

Question 8

Testlet 1 Hotspot

HOTSPOT

You need to ensure that the data engineers are notified if any step in populating the lakehouses fails.

The solution must meet the technical requirements and minimize development effort.

What should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Question 9

Single choice

You have a Fabric workspace that contains a warehouse named Warehouse1. Data is loaded daily into Warehouse1 by using data pipelines and stored procedures.

You discover that the daily data load takes longer than expected.

You need to monitor Warehouse1 to identify the names of users that are actively running queries.

Which view should you use?

A
sys.dm_exec_connections
B
sys.dm_exec_requests
C
queryinsights.long_running_queries
D
queryinsights.frequently_run_queries
E
sys.dm_exec_sessions

Reveal answer details Close answer details

Correct answerE

Question 10

Single choice

In a lakehouse, you notice that a Delta table has thousands of small Parquet files. You need to improve query performance without modifying schema.

What should you run?

A
VACUUM only
B
OPTIMIZE only
C
OPTIMIZE followed by VACUUM
D
CLONE

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Correct answerC

Question 11

Drag & drop

DRAG DROP

You have a Fabric workspace that contains a warehouse named Warehouse1.

In Warehouse1, you create a table named DimCustomer by running the following statement.

You need to set the Customerkey column as a primary key of the DimCustomer table.

Which three code segments should you run in sequence?

To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

stem image

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Question 12

Single choice

You have a Microsoft Power Apps app named App1 that has data stored in Microsoft Dataverse.

You need to access the App1 data by using Fabric.

What should you use?

A
a data pipeline
B
mirroring
C
Dataflow Gen2
D
a shortcut

Reveal answer details Close answer details

Correct answerD

Explanation

To access Power Apps (Dataverse) data from Fabric, use Fabric Link for Dataverse to create a connection from the Power Apps portal to your chosen Fabric workspace. This wizard-driven process links Dataverse tables to a Fabric Lakehouse, which can then be accessed in Fabric for analysis and other tasks, or you can use virtual tables in Dataverse to read Fabric Lakehouse data.

Accessing Data in Fabric: Once the link is established, you can access the Dataverse data in the Lakehouse that was created in the linked Fabric workspace. You can then use the SQL endpoint to query the data.

Note: Steps to Link Dataverse to Fabric:
1. Open the Power Apps Portal: Navigate to
https://make.powerapps.com/.
2. Go to the Tables Area: On the left menu, select Tables.
3. Start the Fabric Link: In the top menu, select Analyze and then click on Link to Microsoft Fabric.
4. Follow the Wizard: A wizard will appear to help you link your Dataverse environment to a Microsoft Fabric workspace.

5. Authenticate: You may need to sign in and authenticate your user account for the connection to be established.

6. Select a Fabric Workspace: Choose a Fabric workspace that is in the same region as your Dataverse environment and is attached to a Fabric Capacity.

7. Complete the Process: The wizard will create a Dataverse link, a Lakehouse, and a SQL endpoint in your chosen Fabric workspace, with Dataverse tables linked via shortcuts.

References:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric

Case study

Case Study 2

Overview
Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide.
Litware also manages an online advertising business for the authors it represents.

Existing Environment. Fabric Environment

Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1. The company has a data engineering team that uses Python for data processing.

Existing Environment. Data Processing
The retail bookstores send sales data at the end of each business day, while the online bookstore constantly provides logs and sales data to a central enterprise resource planning (ERP) system.

Litware implements a medallion architecture by using the following three layers: bronze, silver, and gold.
The sales data is ingested from the ERP system as Parquet les that land in the Files folder in a lakehouse.
Notebooks are used to transform the les in a Delta table for the bronze and silver layers. The gold layer is in a warehouse that has V-Order disabled. Litware has image les of book covers in Azure Blob Storage.
The les are loaded into the Files folder.
Existing Environment. Sales Data

Month-end sales data is processed on the rst calendar day of each month. Data that is older than one month never changes. In the source system, the sales data refreshes every six hours starting at midnight each day. The sales data is captured in a dataflow Gen1 dataflow. When the dataflow runs, new and historical data is captured. The dataflow captures the following elds of the source:

Sales Date
Author
Price
Units
SKU

A table named AuthorSales stores the sales data that relates to each author. The table contains a column named AuthorEmail. Authors authenticate to a guest Fabric tenant by using their email address.
Existing Environment. Security Groups

Litware has the following security groups:

Sales
Fabric Admins
Streaming Admins

Existing Environment. Performance Issues
Business users perform ad-hoc queries against the warehouse. The business users indicate that reports against the warehouse sometimes run for two hours and fail to load as expected. Upon further investigation, the data engineering team receives the following error message when the reports fail to load: "The SQL query failed while running."
The data engineering team wants to debug the issue and nd queries that cause more than one failure.
When the authors have new book releases, there is often an increase in sales activity. This increase slows the data ingestion process. The company's sales team reports that during the last month, the sales data has NOT been up-to-date when they arrive at work in the morning.

Requirements. Planned Changes
Litware recently signed a contract to receive book reviews. The provider of the reviews exposes the data in Amazon Simple Storage Service (Amazon S3) buckets.
Litware plans to manage Search Engine Optimization (SEO) for the authors. The SEO data will be streamed from a REST API.

Requirements. Version Control
Litware plans to implement a version control solution in Fabric that will use GitHub integration and follow the principle of least privilege.
Requirements. Governance Requirements
To control data platform costs, the data platform must use only Fabric services and items. Additional Azure resources must NOT be provisioned.

Requirements. Data Requirements
Litware identi es the following data requirements: Process the SEO data in near-real-time (NRT).
Make the book reviews available in the lakehouse without making a copy of the data.
When a new book cover image arrives in the Files folder, process the image as soon as possible.

Question 13

Testlet 2 Drag & drop

DRAG DROP

You need to ensure that the authors can see only their respective sales data.

How should you complete the statement? To answer, drag the appropriate values the correct targets.

Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content

NOTE: Each correct selection is worth one point.

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Question 14

Single choice

You must configure a Spark job definition to read from Azure SQL Database that has no public network access.

What should you create?

A
Managed private endpoint
B
Dataflow Gen2
C
Linked service
D
On-premises data gateway

Reveal answer details Close answer details

Correct answerA

Question 15

Single choice

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns:

1. BikepointID
2. Street
3. Neighbourhood
4. No_Bikes
5. No_Empty_Docks
6. Timestamp

You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order.

Solution: You use the following code segment:

Does this meet the goal?

A
Yes
B
No

Reveal answer details Close answer details

Correct answerB

Question 16

Single choice

You must monitor long-running warehouse queries and identify the users executing them.

Which view should you use?

A
sys.dm_exec_requests
B
queryinsights.long_running_queries
C
sys.dm_exec_connections
D
sys.dm_exec_sessions

Reveal answer details Close answer details

Correct answerB

Question 17

Single choice

Note: This question is part of a series that presents the same scenario. Each question in the series offers a distinct solution that may fulfill the specified objectives. Some question sets may have multiple valid solutions, while others may not have any correct solutions.

Once you submit an answer to this question, you will not be able to revisit it. Consequently, this question will not appear during the review process.

You are working with a Fabric event stream that loads data into a table named Bike_Location within a KQL database. The table contains the following columns:

1. BikepointID
2. Street
3. Neighbourhood
4. No_Bikes

5. No_Empty_Docks
6. Timestamp

Solution: You use the following code segment:

Does this meet the goal?

A
Yes
B
No

Reveal answer details Close answer details

Correct answerB

Question 18

Hotspot

HOTSPOT

You have a Fabric workspace named Workspace1_DEV that contains the following items:

1. 10 reports
2. Four notebooks
3. Three lakehouses
4. Two data pipelines
5. Two Dataflow Gen1 dataflows
6. Three Dataflow Gen2 dataflows
7. Five semantic models that each has a scheduled refresh policy

You create a deployment pipeline named Pipeline1 to move items from Workspace1_DEV to a new
workspace named Workspace1_TEST.

You deploy all the items from Workspace1_DEV to Workspace1_TEST.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

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Question 19

Hotspot

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.

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Question 20

Single choice

You have a Fabric workspace named Workspace1 that is connected to a GitHub repository named repo1. Workspace1 contains the items shown in the following table.

You modify Semanticmodel1, Semanticmodel2, and Report2.

You need to commit the changes to repo1.

What is the minimum number of commits you should perform?

Reveal answer details Close answer details

Correct answerA

Explanation

To commit the updates for the two semantic models and the second report to the GitHub repository, the minimum number of commits required is one. In Microsoft Fabric's Git integration, you can select multiple changed items simultaneously and commit them in a single batch.

Key Factors for Committing Batch Operations: The Fabric Source Control pane allows you to check the boxes next to all modified items (the two semantic models and the second report) and click Commit once.

Item Support: All the items mentioned (Semantic Models, Power BI Reports, and Dataflow Gen2) are supported for Git integration in Fabric.

Commit Logic: Git integration in Fabric does not force a "one commit per item" rule. As long as the items are in the same workspace and connected to the same branch, they can be grouped into one revision.

References:
https://community.fabric.microsoft.com/t5/Issues/Semantic-Model-and-Report-Syncing-Issues-with-Git-Integration/idi-p/3980544

Question 21

Hotspot

HOTSPOT

You are building a data orchestration pattern by using a Fabric data pipeline named Dynamic Data Copy as shown in the exhibit. (Click the Exhibit tab.)

Dynamic Data Copy does NOT use parametrization.

You need to configure the ForEach activity to receive the list of tables to be copied.

How should you complete the pipeline expression? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

stem image

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Case study

Case Study 2

Overview
Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide.
Litware also manages an online advertising business for the authors it represents.

Existing Environment. Fabric Environment

Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1. The company has a data engineering team that uses Python for data processing.

Sales Date
Author
Price
Units
SKU

Litware has the following security groups:

Sales
Fabric Admins
Streaming Admins

Question 22

Testlet 2 Single choice

What should you do to optimize the query experience for the business users?

A
Enable V-Order.
B
Create and update statistics.
C
Run the VACUUM command.
D
Introduce primary keys.

Reveal answer details Close answer details

Correct answerB

Question 23

Single choice

A semantic model refresh is failing due to missing credentials. You need to authenticate using secrets stored in Azure Key Vault.

Which notebook utility should you use?

A
notebookutils.credentials.getSecret
B
notebookutils.session.get
C
notebookutils.fs.mount
D
notebookutils.secrets.store

Reveal answer details Close answer details

Correct answerA

Question 24

Single choice

You must build a Power Automate flow that activates whenever a new entry is added to a SharePoint list.

Which option represents the appropriate trigger for this flow?

A
When an item is modified
B
When an item is created
C
When an item is deleted
D
When a new document is uploaded

Reveal answer details Close answer details

Correct answerB

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Implementing Data Engineering Solutions Using Microsoft Fabric

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2	Hotspot	7
3	Drag & drop	2