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Microsoft DP-750 Exam Syllabus Topics:

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

Question 1

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

Question 2

You have an Azure Databricks workspace.
You have a streaming table named sales_order that is populated by using a Lakeflow Spark Declarative Pipelines (SDP) pipeline.
You need to create a new streaming table named sales_order_by_city that summarizes sales by city and calculates the total sales per city.
How should you complete the SQL statement? 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.

Question 3

You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a managed Delta table named Sales. Sales stores transaction data and contains the following columns:
* transactionjd (string)
* transaction date (date)
* amount (decimal)
You need to implement the following data quality requirements by using table-level data quality enforcement:
* amount must be greater than 0.
* transaction id must never be null.
* Invalid records must be rejected when data is written to the Sales table.
What should you do?

A. Use a select statement with where conditions to validate the data before querying.
B. Add a not null constraint to transactionjd and a check constraint to amount.
C. Create a view that filters out rows where transactionjd is null or amount is less than or equal to 0.
D. Configure row-level security (RLS) where transactionjd is null or amount is less than or equal to 0.

Question 4

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.

Question 5

You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to implement a daily batch data process that requires complex and highly customized Python transformations. The solution must minimize additional complexity.
What should you include in the solution?

A. a Lakeflow Spark Declarative Pipelines (SDP) pipeline
B. a continuous job in Lakeflow Jobs
C. an Azure Data Factory pipeline that has data flows
D. a Databricks notebook triggered by a job

Solutions: