Free PDF Microsoft - DP-700 - Implementing Data Engineering Solutions Using Microsoft Fabric–Reliable Actual Test Pdf

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Microsoft DP-700 Exam Syllabus Topics:

SectionObjectives
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. PySpark data processing
        • 2. Notebooks in Microsoft 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. Data lineage and cataloging
                • 2. Microsoft Purview integration
                  Manage and monitor data solutions- Monitor pipelines and workloads
                  • 1. Configure alerts and logging
                    • 2. Monitor data pipeline runs
                      - Optimize performance and reliability
                      • 1. Capacity and workload management in Fabric
                        • 2. Spark job optimization
                          Design and implement data ingestion solutions- Integrate external data sources
                          • 1. Connect to Azure data services
                            • 2. Connect to on-premises and SaaS sources
                              - Ingest batch and streaming data into Microsoft Fabric
                              • 1. Use Pipelines for data movement
                                • 2. Use Dataflows Gen2 for ingestion
                                  • 3. Ingest streaming data using Real-Time Analytics

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                                    Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q135-Q140):

                                    NEW QUESTION # 135
                                    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?

                                    Answer: D


                                    NEW QUESTION # 136
                                    You have a Fabric workspace that contains a lakehouse named Lakehouse1. Data is ingested into Lakehouse1 as one flat table. The table contains the following columns.

                                    You plan to load the data into a dimensional model and implement a star schema. From the original flat table, you create two tables named FactSales and DimProduct. You will track changes in DimProduct.
                                    You need to prepare the data.
                                    Which three columns should you include in the DimProduct table? Each correct answer presents part of the solution.
                                    NOTE: Each correct selection is worth one point.

                                    Answer: B,C,F

                                    Explanation:
                                    In a star schema, the DimProduct table serves as a dimension table that contains descriptive attributes about products. It will provide context for the FactSales table, which contains transactional data. The following columns should be included in the DimProduct table:
                                    ProductName: The ProductName is an important descriptive attribute of the product, which is needed for analysis and reporting in a dimensional model.
                                    ProductColor: ProductColor is another descriptive attribute of the product. In a star schema, it makes sense to include attributes like color in the dimension table to help categorize products in the analysis.
                                    ProductID: ProductID is the primary key for the DimProduct table, which will be used to join the FactSales table to the product dimension. It ' s essential for uniquely identifying each product in the model.


                                    NEW QUESTION # 137
                                    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 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 # 138
                                    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?

                                    Answer: B


                                    NEW QUESTION # 139
                                    You are developing a data pipeline named Pipeline1.
                                    You need to add a Copy data activity that will copy data from a Snowflake data source to a Fabric warehouse. Which option from the Settings tab of the Copy data activity must you configure?

                                    Answer: A


                                    NEW QUESTION # 140
                                    ......

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