Microsoft

DP-700 Free Practice Questions — Page 4

Question 29

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 - 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 files that land in the Files folder in a lakehouse. Notebooks are used to transform the files 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 files of book covers in Azure Blob Storage. The files are loaded into the Files folder. Existing Environment. Sales Data Month-end sales data is processed on the first 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 fields 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 find 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 identifies 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. You need to create a workflow for the new book cover images. Which two components should you include in the workflow? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A. a time-based schedule
B. a streaming dataflow
C. a blob storage action
D. a data pipeline
E. a notebook that uses Apache Spark Structured Streaming
F. a reflex item
Show Answer
Correct Answer: D, F
Explanation:
The requirement is to process images as soon as they arrive in the lakehouse Files folder using Fabric-only, event-driven components. A data pipeline provides native orchestration for processing steps, and a Reflex item (now called Activator) enables event-based triggering when new files land in OneLake/Files. Together they support immediate, Fabric-native processing without schedules or external Azure resources.

Question 30

You have a Fabric workspace that contains a warehouse named Warehouse1. You have an on-premises Microsoft SQL Server database named Database1 that is accessed by using an on-premises data gateway. You need to copy data from Database1 to Warehouse1. Which item should you use?

A. a data pipeline
B. an Apache Spark job definition
C. a streaming dataflow
D. a notebook
Show Answer
Correct Answer: A
Explanation:
To copy data from an on-premises SQL Server database to a Fabric Warehouse using an on-premises data gateway, the appropriate choice is a data pipeline. Fabric data pipelines are designed for batch data movement and natively support connections through the on-premises data gateway, making them the standard and supported option for this scenario.

Question 31

DRAG DROP - You have a Fabric workspace that contains an eventhouse named Eventhouse1. In Eventhouse1, you plan to create a table named DeviceStreamData in a KQL database. The table will contain data based on the following sample. You need to use a KQL query to develop the solution for Eventhouse1. 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.

Illustration for DP-700 question 31 Illustration for DP-700 question 31
Show Answer
Correct Answer: 1. .create table EventStreamData ( 2. TimeStamp:datetime, DeviceId:string 3. StreamData:dynamic )
Explanation:
The table must first be created in the KQL database. The schema defines TimeStamp and DeviceId as scalar columns, while StreamData is stored as a dynamic column to hold the JSON array shown in the sample. These three segments together form the correct create table statement in the required order.

Question 32

HOTSPOT - You have a table in a Fabric lakehouse that contains the following data. You have a notebook that contains 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.

Illustration for DP-700 question 32 Illustration for DP-700 question 32 Illustration for DP-700 question 32
Show Answer
Correct Answer: Line 01: Yes Line 02: No Line 03: No
Explanation:
Line 01 uses when/isNull or empty string to replace with "Unknown". Line 02 uses split(Email, "@").getItem(1), which returns the part after @, not before. Line 03 drops duplicates by OrderDate, not by Year, so it does not keep only the first occurrence per year.

Question 33

You have a Fabric workspace that contains an eventstream named EventStream1. EventStream1 outputs events to a table named Table1 in a lakehouse. The streaming data is sourced from motorway sensors and represents the speed of cars. You need to add a transformation to EventStream1 to average the car speeds. The speeds must be grouped by non-overlapping and contiguous time intervals of one minute. Each event must belong to exactly one window. Which windowing function should you use?

A. sliding
B. hopping
C. tumbling
D. session
Show Answer
Correct Answer: C
Explanation:
The requirement specifies non-overlapping, contiguous one-minute intervals where each event belongs to exactly one window. Tumbling windows partition the event stream into fixed-size, back-to-back intervals with no overlap, which matches this behavior. Sliding and hopping windows can overlap, and session windows are based on activity gaps rather than fixed time intervals.

Question 34

You are implementing a medallion architecture in a Fabric lakehouse. You plan to create a dimension table that will contain the following columns: • ID • CustomerCode • CustomerName • CustomerAddress • CustomerLocation • ValidFrom • ValidTo You need to ensure that the table supports the analysis of historical sales data by customer location at the time of each sale. Which type of slowly changing dimension (SCD) should you use?

A. Type 2
B. Type 0
C. Type 1
D. Type 3
Show Answer
Correct Answer: A
Explanation:
SCD Type 2 preserves full history by creating a new row for each change and using ValidFrom/ValidTo dates. This allows analyzing sales by the customer location as it existed at the time of each sale, which is the stated requirement.

Question 35

HOTSPOT - Your company has three newly created data engineering teams named Team1, Team2, and Team3 that plan to use Fabric. The teams have the following personas: • Team1 consists of members who currently use Microsoft Power BI. The team wants to transform data by using by a low-code approach. • Team2 consists of members that have a background in Python programming. The team wants to use PySpark code to transform data. • Team3 consists of members who currently use Azure Data Factory. The team wants to move data between source and sink environments by using the least amount of effort. You need to recommend tools for the teams based on their current personas. What should you recommend for each team? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Illustration for DP-700 question 35
Show Answer
Correct Answer: Team1: Dataflow Gen2 dataflow Team2: Notebooks Team3: Data pipelines
Explanation:
Team1 needs low-code data transformation familiar to Power BI users, which is provided by Dataflow Gen2. Team2 prefers Python and PySpark, best supported through Fabric Notebooks. Team3 focuses on simple data movement similar to Azure Data Factory, which aligns with Data pipelines.

Question 36

HOTSPOT - You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains a table named Customer. Customer contains the following data. You have an internal Microsoft Entra user named User1 that has an email address of . You need to provide User1 with access to the Customer table. The solution must prevent User1 from accessing the CreditCard column. How should you complete the statement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Illustration for DP-700 question 36 Illustration for DP-700 question 36
Show Answer
Correct Answer: SELECT [User1]
Explanation:
Use column-level security in Fabric Warehouse. Grant SELECT on only the allowed columns (excluding CreditCard) to the internal Entra user. The GRANT must be SELECT, and the principal is the database user [User1].

Question 37

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. 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: • The data engineers must have read and write access to all the lakehouses, including the underlying files. • The data analysts must only have read access to the Delta tables in the gold layer. • The data analysts must NOT have access to the data in the bronze and silver layers. • The data engineers must be able to commit changes to source control in WorkspaceA. You need to ensure that WorkspaceA can be configured for source control. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A. From Tenant setting, set Users can synchronize workspace items with their Git repositories to Enabled.
B. From Tenant setting, set Users can sync workspace items with GitHub repositories to Enabled.
C. Configure WorkspaceA to use a Premium Per User (PPU) license.
D. Assign WorkspaceA to Cap1.
Show Answer
Correct Answer: A, D
Explanation:
To enable Git integration for WorkspaceA using Azure Repos, Fabric requires that tenant-level Git synchronization be enabled and that the workspace run on a Fabric capacity. Enabling the tenant setting allows users to sync workspace items with Git repositories, and assigning WorkspaceA to the existing F64 capacity (Cap1) is a prerequisite for configuring source control. GitHub-specific settings and PPU licensing are not required.

Question 38

You have a Fabric workspace that contains a data pipeline named Pipeline1 as shown in the exhibit. (Click the Exhibit tab.) What will occur the next time Pipeline1 runs?

A. Copy_kdi will run first, and then Execute procedure1 will run.
B. Execute procedure1 will run first, and then Copy_kdi will run.
C. Execute procedure1 will run and Copy_kdi will be skipped.
D. Copy_kdi will run and Execute procedure1 will be skipped.
E. Both activities will run simultaneously.
F. Both activities will be skipped.
Show Answer
Correct Answer: D
Explanation:
The Execute procedure1 activity is shown as deactivated (crossed-circle icon). Deactivated activities are skipped during pipeline execution. Copy_kdi is active, so it will run, while Execute procedure1 will be skipped.

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