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Microsoft DP-700 Exam Syllabus Topics:

SectionWeightObjectives
Ingest and transform data30–35%- Ingest data
  • 1. Ingest data using Eventstreams
    • 2. Ingest data using pipelines
      • 3. Ingest data using Dataflows Gen2
        - Design and implement data loading patterns
        • 1. Design streaming data loading patterns
          • 2. Prepare data for dimensional models
            • 3. Design full and incremental data loads
              - Transform data
              • 1. Transform data using PySpark
                • 2. Clean, denormalize, and aggregate data
                  • 3. Transform data using KQL
                    • 4. Transform data using SQL
                      - Orchestrate data operations
                      • 1. Use parameters and dynamic expressions
                        • 2. Orchestrate with notebooks and pipelines
                          • 3. Implement schedules and triggers
                            Implement and manage an analytics solution30–35%- Configure workspace settings
                            • 1. Configure Spark workspace settings
                              • 2. Configure domain workspace settings
                                • 3. Configure Microsoft Fabric workspace settings
                                  • 4. Configure Dataflows Gen2 settings
                                    • 5. Configure OneLake workspace settings
                                      - Manage data storage
                                      • 1. Implement data mirroring
                                        • 2. Choose appropriate data stores
                                          • 3. Create and manage OneLake shortcuts
                                            - Manage data lifecycle and governance
                                            • 1. Implement data governance with Microsoft Purview
                                              • 2. Implement data retention and archiving
                                                • 3. Manage data access and security
                                                  Monitor and optimize an analytics solution30–35%- Monitor analytics solutions
                                                  • 1. Monitor Fabric items and activities
                                                    • 2. Monitor semantic model refreshes
                                                      • 3. Configure alerts and notifications
                                                        • 4. Monitor data ingestion and transformation
                                                          - Troubleshoot issues
                                                          • 1. Identify and resolve notebook and Spark errors
                                                            • 2. Identify and resolve Dataflow errors
                                                              • 3. Identify and resolve storage and query errors
                                                                • 4. Identify and resolve pipeline errors
                                                                  - Optimize performance
                                                                  • 1. Optimize pipelines and data flows
                                                                    • 2. Optimize Spark and query performance
                                                                      • 3. Optimize Lakehouse and data warehouse performance
                                                                        • 4. Optimize storage efficiency

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                                                                          Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q66-Q71):

                                                                          NEW QUESTION # 66
                                                                          You have a Fabric workspace that contains a data pipeline named Pipeline! as shown in the exhibit.
                                                                          (Click the Exhibit tab.) What will occur the next time Pipelinel tuns?

                                                                          Answer: F


                                                                          NEW QUESTION # 67
                                                                          You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse2. A team of data analysts has Viewer role access to Workspace1. You create a table by running the following statement.

                                                                          You need to ensure that the team can view only the first two characters and the last four characters of the Creditcard attribute.
                                                                          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:

                                                                          Explanation:


                                                                          NEW QUESTION # 68
                                                                          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:
                                                                          The data from which shortcuts will be retrieved from the cache?

                                                                          Answer: E

                                                                          Explanation:
                                                                          When the cache for shortcuts is enabled in Fabric, the data retrieval is governed by the caching behavior, which generally retains data for a specific period after it was last accessed. The data from the shortcuts will be retrieved from the cache if the data is stored in locations that support caching. Here's a breakdown based on the data's location:
                                                                          Products: The ProductFile is stored in Azure Data Lake Storage Gen2 (storage1). Since Azure Data Lake is a supported storage system in Fabric and the file is relatively small (50 MB), this data is most likely cached and can be retrieved from the cache.
                                                                          Stores: The StoreFile is stored in Amazon S3 (storage2), and even though it is stored in a different cloud provider, Fabric can cache data from Amazon S3 if caching is enabled. This data (25 MB) is likely cached and retrievable.
                                                                          Trips: The TripsFile is stored in Amazon S3 (storage2) and is significantly larger (2 GB) compared to the other files. While Fabric can cache data from Amazon S3, the larger size of the file (2 GB) may exceed typical cache sizes or retention windows, causing this file to likely be retrieved directly from the source instead of the cache.


                                                                          NEW QUESTION # 69
                                                                          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:
                                                                          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?

                                                                          Answer: B

                                                                          Explanation:
                                                                          This code does not meet the goal because this is an SQL-like query and cannot be executed in KQL, which is required for the database.
                                                                          Correct code should look like:


                                                                          NEW QUESTION # 70
                                                                          You need to recommend a solution to resolve the MAR1 connectivity issues. The solution must minimize development effort. What should you recommend?

                                                                          Answer: A

                                                                          Explanation:
                                                                          Topic 2, Litware, IncCase 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.


                                                                          NEW QUESTION # 71
                                                                          ......

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