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Microsoft DP-700 Exam Syllabus Topics:

SectionObjectives
Manage and monitor data solutions- Monitor pipelines and workloads
  • 1. Configure alerts and logging
    • 2. Monitor data pipeline runs
      - Optimize performance and reliability
      • 1. Spark job optimization
        • 2. Capacity and workload management in Fabric
          Secure and govern data in Microsoft Fabric- Implement data security
          • 1. Row-level security and column-level security
            • 2. Workspace and item-level permissions
              - Data governance and compliance
              • 1. Microsoft Purview integration
                • 2. Data lineage and cataloging
                  Develop data transformation solutions- Data modeling and lakehouse transformation
                  • 1. Delta Lake optimization
                    • 2. Medallion architecture (Bronze/Silver/Gold)
                      - Transform data using Spark in Fabric
                      • 1. Notebooks in Microsoft Fabric
                        • 2. PySpark data processing
                          Design and implement data ingestion solutions- Ingest batch and streaming data into Microsoft Fabric
                          • 1. Ingest streaming data using Real-Time Analytics
                            • 2. Use Pipelines for data movement
                              • 3. Use Dataflows Gen2 for ingestion
                                - Integrate external data sources
                                • 1. Connect to Azure data services
                                  • 2. Connect to on-premises and SaaS sources

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                                    Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q32-Q37):

                                    NEW QUESTION # 32
                                    You need to recommend a Fabric streaming solution that will use the sources shown in the following table.

                                    The solution must minimize development effort.
                                    What should you include in the recommendation for each source? To answer, select the appropriate options in the answer area.
                                    NOTE: Each correct selection is worth one point.

                                    Answer:

                                    Explanation:

                                    Explanation:


                                    NEW QUESTION # 33
                                    You have a Fabric warehouse named DW1 that contains a Type 2 slowly changing dimension (SCD) dimension table named DimCustomer. DimCustomer contains 100 columns and 20 million rows. The columns are of various data types, including int, varchar, date, and varbinary.
                                    You need to identify incoming changes to the table and update the records when there is a change. The solution must minimize resource consumption.
                                    What should you use to identify changes to attributes?

                                    Answer: B


                                    NEW QUESTION # 34
                                    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?

                                    Answer: A

                                    Explanation:
                                    This code does not meet the goal because it uses order by, which is not valid in KQL. The correct term in KQL is sort by.
                                    Correct code should look like:


                                    NEW QUESTION # 35
                                    You need to ensure that the authors can see only their respective sales data.
                                    How should you complete the statement? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.

                                    Answer:

                                    Explanation:

                                    Explanation:


                                    NEW QUESTION # 36
                                    You have a Fabric workspace that contains a data pipeline named Pipeline! as shown in the exhibit.

                                    Answer: A


                                    NEW QUESTION # 37
                                    ......

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