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Microsoft DP-750 Exam Syllabus Topics:

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

                                                      Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

                                                      Question 1

                                                      Which SCD type should you use to support the planned data modeling changes? To answer, drag the appropriate types to the correct issues. Each type 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.


                                                      Question 2

                                                      You have an Azure Databricks workspace that is enabled for Unity Catalog and contains:
                                                      * A catalog named Finance
                                                      * A schema named Purchases in the Finance catalog
                                                      * A table named Transactions in the Purchases schema
                                                      You need to ensure that a user named finance_user can query the Transactions table. The solution must follow the principle of least privilege.
                                                      Which permission should you grant to finance_user for each object? To answer, drag the appropriate permissions to the correct objects. Each permission 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.


                                                      Question 3

                                                      You have an Azure Databricks workspace that is enabled for Unity Catalog.
                                                      You need to recommend a pipeline that ingests files from cloud storage, performs cleansing and enrichment transformations, and writes created Delta tables for analytics. The solution must minimize development effort and provide built-in monitoring and automatic retries.
                                                      What should you include in the recommendation?

                                                      A. an Azure Data Factory pipeline that uses data flows
                                                      B. a Databricks notebook triggered by a scheduled job
                                                      C. an Apache Spark Structured Streaming job
                                                      D. a Lakeflow Spark Declarative Pipelines (SDPJ pipeline


                                                      Question 4

                                                      You have an Azure Databricks workspace that contains a Delta table named Customer.
                                                      A job named Job1 performs frequent upserts into Customer.
                                                      You discover that Job1 has created many small Parquet files in Customer, and the small files are degrading query performance.
                                                      You need to improve query performance for the current data already stored in Customer. The solution must not affect the travel for the Customer table.
                                                      What should you do?

                                                      A. Set the delta.autoOptimize.optimizeWrite Apache Spark configuration to true.
                                                      B. Run the OPTIMIZE command on the Customer table.
                                                      C. Set the delta.deletedFileRetentionDuration table property to 1 day.
                                                      D. Run the VACUUM command on the Customer table.


                                                      Question 5

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

                                                      A. the Azure Developer CLI (azd)
                                                      B. the Databricks CLI
                                                      C. the Azure Command-Line Interface (CLI)
                                                      D. Git folders


                                                      Solutions:

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

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