Online DP-700 Exam Dumps Help You Build Confidence

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Practicing with Microsoft Certified: Fabric Data Engineer Associate DP-700 exam dumps questions can help you build confidence and reduce exam anxiety. By familiarizing yourself with the types of questions you can expect to see on the DP-700 Microsoft Fabric Data Engineer exam and mastering the concepts and skills required to answer them, you can approach the exam with greater confidence and a sense of calm. Besides, DP-700 dumps questions can help you achieve this level of knowledge and confidence. Study free Microsoft DP-700 exam dumps below.

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1. Topic 2, Litware, Inc



Case Study

Overview

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 implement the solution for the book reviews.

Which should you do?

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

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.



3. You have a Fabric workspace that contains a warehouse named DW1. DW1 is loaded by using a notebook named Notebook1.

You need to identify which version of Delta was used when Notebook1 was executed.

What should you use?

4. You have a Fabric workspace named Workspace1 that contains a data pipeline named Pipeline1 and a lakehouse named Lakehouse1.

You have a deployment pipeline named deployPipeline1 that deploys Workspace1 to Workspace2.

You restructure Workspace1 by adding a folder named Folder1 and moving Pipeline1 to Folder1.

You use deployPipeline1 to deploy Workspace1 to Workspace2.

What occurs to Workspace2?

5. 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:

- BikepointID

- Street

- Neighbourhood

- No_Bikes

- No_Empty_Docks

- 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?

6. You have a Fabric capacity that contains a workspace named Workspace1. Workspace1 contains a lake house named Lakehouse1, a data pipeline, a notebook, and several Microsoft Power BI reports.

A user named User1 wants to use SQL to analyze the data in Lakehouse1.

You need to configure access for User1.

The solution must meet the following requirements:

- Provide User1 with read access to the table data in Lakehouse1.

- Prevent User1 from using Apache Spark to query the underlying files in Lakehouse1.

- Prevent User1 from accessing other items in Workspace1.

What should you do?

7. 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.



8. You have an Azure Data Lake Storage Gen2 account named storage1 and an Amazon S3 bucket named storage2.

You have the Delta Parquet files shown in the following table.





You have a Fabric workspace named Workspace1 that has the cache for shortcuts enabled.

Workspace1 contains a lakehouse named Lakehouse1.

Lakehouse1 has the following shortcuts:

- A shortcut to ProductFile aliased as Products

- A shortcut to StoreFile aliased as Stores

- A shortcut to TripsFile aliased as Trips

The data from which shortcuts will be retrieved from the cache?

9. You have a Fabric workspace named Workspace1.

You plan to integrate Workspace1 with Azure DevOps.

You will use a Fabric deployment pipeline named deployPipeline1 to deploy items from Workspace1 to higher environment workspaces as part of a medallion architecture. You will run deployPipeline1 by using an API call from an Azure DevOps pipeline.

You need to configure API authentication between Azure DevOps and Fabric.

Which type of authentication should you use?

10. You have two Fabric workspaces named Workspace1 and Workspace2.

You have a Fabric deployment pipeline named deployPipeline1 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?


 

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