Microsoft DP-750 Q&A - in .pdf

  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
  • Updated: Aug 10, 2026
  • Q & A: 93 Questions and Answers
  • Printable Microsoft DP-750 PDF Format. It is an electronic file format regardless of the operating system platform.
  • PDF Price: $59.99
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  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
  • Q & A: 93 Questions and Answers
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Microsoft DP-750 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Configure and manage Azure Databricks environments15-20%- Security and authentication setup
  • 1. Service principals and managed identities
    • 2. Azure Key Vault integration
      • 3. Access control for compute resources
        - Workspace and compute configuration
        • 1. Cluster types and configuration (job, all-purpose, serverless)
          • 2. Runtime, Spark, and Photon configuration
            • 3. Autoscaling, termination, and performance tuning
              Topic 2: Prepare and process data30-35%- Data quality and validation
              • 1. Pipeline expectations and data quality constraints
                • 2. Handling nulls, duplicates, and missing data
                  • 3. Schema enforcement and validation rules
                    - Data ingestion
                    • 1. Batch ingestion using COPY INTO and CTAS
                      • 2. Streaming ingestion using Spark Structured Streaming
                        • 3. Auto Loader and CDC ingestion patterns
                          - Data transformation and modeling
                          • 1. SQL and PySpark transformations
                            • 2. Joins, aggregations, and normalization/denormalization
                              • 3. Delta Lake table design and SCD patterns
                                Topic 3: Secure and govern data using Unity Catalog15-20%- Data governance fundamentals
                                • 1. Catalog, schema, and table management
                                  • 2. Data lineage and auditing
                                    - Access control and policies
                                    • 1. Row-level and column-level security
                                      • 2. Tags and policy enforcement
                                        • 3. Attribute-based access control (ABAC)
                                          Topic 4: Deploy and manage data pipelines and workloads30-35%- Operational reliability
                                          • 1. Error handling and retries
                                            • 2. Monitoring and logging (Azure Monitor integration)
                                              - Pipeline design and orchestration
                                              • 1. Databricks Jobs and Workflows
                                                • 2. Notebook-based vs declarative pipelines
                                                  - 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 Apache Spark DataFrame named salesDF that contains the following columns:
                                                      * Product
                                                      * Region
                                                      * Sales
                                                      * Date
                                                      You need to create a pivot table that shows the total sales by product for each region.
                                                      How should you complete the PySpark code segment? To answer, drag the appropriate values to 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.


                                                      2. You need to deploy Declarative Automation Bundles to a development environment. The solution must support automated and repeatable deployments across environments.
                                                      What should you use?

                                                      A) Git folders
                                                      B) the Databricks SDK for Python
                                                      C) the Jobs UI
                                                      D) the Databricks CLI


                                                      3. You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1. Job1 contains multiple tasks.
                                                      Failures of non-critical tasks must be logged but must NOT trigger notifications. Notifications must be triggered only when critical tasks have failed, and Job1 has completed You need to configure the job alerting behavior.
                                                      What should trigger a notification?

                                                      A) a task failure
                                                      B) a job failure
                                                      C) job success
                                                      D) task success


                                                      4. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders.
                                                      You load the Orders table into an Apache Spark DataFrame named df.
                                                      You need to create a DataFrame that excludes rows where the order amount is null.
                                                      Solution: You run the following expression.
                                                      df.dropna(subset=[ " order_amount " ])
                                                      Does this meet the goal?

                                                      A) Yes
                                                      B) No


                                                      5. You have an Azure Databricks workspace that is enabled for Unity Catalog.
                                                      You plan to create a job in Lakeflow Jobs named Job1 that:
                                                      * Ingests data from cloud storage
                                                      * Runs two independent transformation tasks
                                                      The transformation tasks must run only after the ingestion completes and must run in parallel.
                                                      You need to design the task logic for Job1.
                                                      What should you configure?

                                                      A) two ingestion tasks, each followed by a transformation task
                                                      B) independent tasks with no defined dependencies
                                                      C) One ingestion task with two parallel downstream transformation tasks
                                                      D) a single task that performs ingestion and transformations sequentially


                                                      Solutions:

                                                      Question # 1
                                                      Answer: Only visible for members
                                                      Question # 2
                                                      Answer: D
                                                      Question # 3
                                                      Answer: B
                                                      Question # 4
                                                      Answer: A
                                                      Question # 5
                                                      Answer: C

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