Microsoft DP-750 Q&A - in .pdf

  • DP-750 pdf
  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
  • Updated: Aug 25, 2026
  • Q & A: 93 Questions and Answers
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  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
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  • DP-750 Testing Engine
  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
  • Updated: Aug 25, 2026
  • Q & A: 93 Questions and Answers
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DP-750 Practice Dumps

Microsoft DP-750 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Secure and govern data using Unity Catalog15-20%- Access control and policies
  • 1. Attribute-based access control (ABAC)
    • 2. Tags and policy enforcement
      • 3. Row-level and column-level security
        - Data governance fundamentals
        • 1. Data lineage and auditing
          • 2. Catalog, schema, and table management
            Topic 2: Configure and manage Azure Databricks environments15-20%- Security and authentication setup
            • 1. Azure Key Vault integration
              • 2. Service principals and managed identities
                • 3. Access control for compute resources
                  - Workspace and compute configuration
                  • 1. Runtime, Spark, and Photon configuration
                    • 2. Cluster types and configuration (job, all-purpose, serverless)
                      • 3. Autoscaling, termination, and performance tuning
                        Topic 3: Prepare and process data30-35%- Data transformation and modeling
                        • 1. SQL and PySpark transformations
                          • 2. Joins, aggregations, and normalization/denormalization
                            • 3. Delta Lake table design and SCD patterns
                              - Data ingestion
                              • 1. Batch ingestion using COPY INTO and CTAS
                                • 2. Auto Loader and CDC ingestion patterns
                                  • 3. Streaming ingestion using Spark Structured Streaming
                                    - Data quality and validation
                                    • 1. Pipeline expectations and data quality constraints
                                      • 2. Handling nulls, duplicates, and missing data
                                        • 3. Schema enforcement and validation rules
                                          Topic 4: Deploy and manage data pipelines and workloads30-35%- Pipeline design and orchestration
                                          • 1. Databricks Jobs and Workflows
                                            • 2. Notebook-based vs declarative pipelines
                                              - Operational reliability
                                              • 1. Error handling and retries
                                                • 2. Monitoring and logging (Azure Monitor integration)
                                                  - Lakehouse architecture operations
                                                  • 1. Delta Lake optimization and clustering strategies
                                                    • 2. Delta Live Tables pipelines

                                                      Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

                                                      1. You have an Azure Databricks workspace that contains an all-purpose cluster named Cluster! You need to configure Cluster1 to meet the following requirements;
                                                      * The cluster must scale up automatically when workloads increase.
                                                      * The cluster must scale down automatically when workloads decrease.
                                                      The solution must minimize costs.
                                                      Which two actions should you perform? Each correct answer presents part of the solution.
                                                      NOTE: Each correct selection is worth one point.

                                                      A) Apply a compute policy that enables users to manage the cluster settings.
                                                      B) Specify a fixed number of workers.
                                                      C) Disable Photon acceleration.
                                                      D) Configure Cluster1 to terminate after 30 minutes of inactivity.
                                                      E) Enable autoscaling for Cluster1.


                                                      2. You need to develop the task logic for a new job in Lakeflow Jobs that processes telemetry data.
                                                      Each task must contain only the appropriate logic for its step in the pipeline. The solution must support the planned changes and meet the data ingestion and processing requirements.
                                                      What should you do?

                                                      A) Use a single Databricks notebook task that performs ingestion, cleansing, and curation in one script.
                                                      B) Create separate tasks for ingestion, cleansing, and curation.
                                                      C) Create three tasks that each contains the identical logic and use task retries.
                                                      D) Use a single SQL task that performs ingestion, cleansing, and curation by running merge commands.


                                                      3. You use Declarative Automation Bundles to manage two jobs and an app.
                                                      You need to deploy the bundle to development and production environments. The solution must meet the following requirements:
                                                      * Deploy the app to both environments.
                                                      * Deploy only one job to development.
                                                      * Minimize administrative effort.
                                                      What should you use?

                                                      A) a resources node in a databricks.yml file
                                                      B) a targets node in a databricks.yml file
                                                      C) a variables node in a databricks.yml file
                                                      D) separate databricks.yml files for each environment


                                                      4. You have an Azure Databricks workspace named Workspace1 that contains a lakehouse and is enabled for Unity Catalog.
                                                      You have a connection to a Microsoft SQL Server database named DB1.
                                                      You need to expose the schemas and tables of DB1 to meet the following requirements:
                                                      * The schemas and tables can be queried in Databricks.
                                                      * The schemas and tables appear alongside other Unity Catalog objects.
                                                      * The data is NOT copied into Databricks-managed storage.
                                                      Solution: You create a foreign catalog in Catalog Explorer.
                                                      Does this meet the goal?

                                                      A) No
                                                      B) Yes


                                                      5. You use Databricks Asset Bundles to manage two jobs and an app.
                                                      You need to deploy the bundle to development and production environments. The solution must meet the following requirements
                                                      * Deploy the app to both environments.
                                                      * Deploy only one job to development.
                                                      * Minimize administrative effort.
                                                      What should you use?

                                                      A) a resources node in a databricks.yml file
                                                      B) a targets node in a databricks.yml file
                                                      C) a variables node in a databricks.yml file
                                                      D) separate databricks.yml files for each environment


                                                      Solutions:

                                                      Question # 1
                                                      Answer: D,E
                                                      Question # 2
                                                      Answer: B
                                                      Question # 3
                                                      Answer: B
                                                      Question # 4
                                                      Answer: B
                                                      Question # 5
                                                      Answer: B

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