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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q58-Q63):

NEW QUESTION # 58
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?

A. Yes
B. no

Answer: A

Explanation:
Filter Condition: It correctly filters rows where Neighbourhood is "Sands End" and No_Bikes is greater than or equal to 15.
Sorting: The sorting is explicitly done by No_Bikes in ascending order using sort by No_Bikes asc.
Projection: It projects the required columns (BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp), which minimizes the data returned for consumption.

NEW QUESTION # 59
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains a table named DimCustomers. DimCustomers contains the following columns:
* CustomerName
* CustomerlD
* BirthDate
* Email
You need to configure security to meet the following requirements:
* BirthDate in DimCustomer must be masked and display 1900-01-01.
* Email 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.

Answer:

Explanation:

NEW QUESTION # 60
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 Trigger the process when a new file is added.
Provide the highest throughput.
Which type of item should you use to ingest the data?

A. Dataflow Gen2
B. KQL queryset
C. Environment
D. Data pipeline

Answer: D

Explanation:
To efficiently ingest large data files (500 GB each) into Lakehouse1 with high throughput and trigger the process when a new file is added, a Data pipeline is the most suitable solution. Data pipelines in Fabric are ideal for orchestrating data movement and can be configured to automatically trigger based on file arrivals or other events. This solution meets both requirements: ingesting the data without transformations (since you just need to copy the data) and triggering the process when new files are added.
Topic 1, Litware, Inc
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:
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:
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:

NEW QUESTION # 61
You are building a Fabric notebook named MasterNotebookl in a workspace. MasterNotebookl contains the following code.

You need to ensure that the notebooks are executed in the following sequence:
1. Notebook_03
2. Notebook.Ol
3. Notebook_02
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A. Move the declaration of Notebook_03 to the top of the Directed Acyclic Graph (DAG) definition.
B. Add dependencies to the execution of Notebook_03.
C. Move the declaration of Notebook_02 to the bottom of the Directed Acyclic Graph (DAG) definition.
D. Change the concurrency to 3.
E. Add dependencies to the execution of Note boo k_02.
F. Split the Directed Acyclic Graph (DAG) definition into three separate definitions.

Answer: A,E

NEW QUESTION # 62
Exhibit.

You have a Fabric workspace that contains a write-intensive warehouse named DW1. DW1 stores staging tables that are used to load a dimensional model. The tables are often read once, dropped, and then recreated to process new data.
You need to minimize the load time of DW1.
What should you do?

A. Disable V-Order.
B. Enable V-O-der.
C. Drop statistics.
D. Create statistics.

Answer: A

NEW QUESTION # 63
......

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