DP-700 Free Practice Questions — Page 6

Question 51

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?

Question 52

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?

Question 53

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.

Question 54

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.

Question 55

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.

Question 56

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?

Question 57

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?

Question 58

You are building a Fabric notebook named MasterNotebook1 in a workspace. MasterNotebook1 contains the following code. You need to ensure that the notebooks are executed in the following sequence: 1. Notebook_03 2. Notebook_01 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.

Question 59

You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1. Workspace1 contains the following items: • A Dataflow Gen2 dataflow that copies data from an on-premises Microsoft SQL Server database to Lakehouse1 • A notebook that transforms files and loads the data to Lakehouse1 • A data pipeline that loads a CSV file to Lakehouse1 You need to develop an orchestration solution in Fabric that will load each item one after the other. The solution must be scheduled to run every 15 minutes. Which type of item should you use?

Question 60

You have a Fabric workspace that contains a lakehouse named Lakehouse1. You plan to create a data pipeline named Pipeline1 to ingest data into Lakehouse1. You will use a parameter named param1 to pass an external value into Pipeline1. The param1 parameter has a data type of int. You need to ensure that the pipeline expression returns param1 as an int value. How should you specify the parameter value?