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Microsoft DP-750 Exam Overview:
| Certification Vendor: | Microsoft |
| Exam Name: | Implementing Data Engineering Solutions Using Azure Databricks |
| Exam Number: | DP-750 |
| Related Certifications: | Microsoft Certified: Azure Data Engineer Associate (DP-203) Microsoft Certified: Fabric Data Engineer Associate (DP-700) |
| Exam Duration: | 100 minutes |
| Available Languages: | English |
| Exam Format: | Multiple choice, Case studies, Scenario-based questions, Interactive items |
| Passing Score: | 700 |
| Recommended Training: | Microsoft Learn DP-750 Study Guide DP-750 Training Course (DP-750T00) |
| Exam Registration: | Pearson VUE Exam Scheduling Official Microsoft Certification Page |
| Sample Questions: | Microsoft DP-750 Sample Questions |
| Exam Way: | Online proctored exam via Pearson VUE |
| Pre Condition: | Recommended experience with Azure Databricks, SQL, Python, and basic Azure services (Entra ID, Data Factory, Key Vault, Azure Storage). |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/implementing-data-engineering-solutions-using-azure-databricks/ |
Microsoft DP-750 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Secure and govern data using Unity Catalog | 15-20% | - Access control and policies
|
| Prepare and process data | 30-35% | - Data transformation and modeling
|
| Configure and manage Azure Databricks environments | 15-20% | - Workspace and compute configuration
|
| Deploy and manage data pipelines and workloads | 30-35% | - Pipeline design and orchestration
|
Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:
1. You have an Azure Databricks workspace.
You need to ingest streaming data from Azure Event Hubs by using Apache Spark Structured Streaming The solution must authenticate to Event Hubs and read the event payload.
How should you complete the PySpark code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
2. 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-fillna(0, subset=[ ' order_amount ' ])
Does this meet the goal?
A) No
B) Yes
3. You have an Azure Databricks workspace that is enabled for Unity Catalog You have a complex job named Job1 that contains eight tasks. Job! takes multiple hours to complete During the last job run, the final task fails due to a transient issue.
You need to retry the last task without rerunning tasks that have already completed.
What should you do?
A) Disable and reenable the job schedule.
B) Repair the current job run.
C) Restart Job!
D) Update the job parameters.
4. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains two Delta tables named Table1 and Table2 of the same data type.
Table1 contains a column named Columnl. Table2 contains a column named Column2. You run the following query.
SELECT Column1
FROM Table1
GROUP BY Column1
HAVING COUNT( " ) > 1
INTERSECT
SELECT C0lumn2
FROM Table2
GROUP BY Column2
HAVING COUNT( ' ) > 1;
What occurs when you run the query?
A) Values appear in either table more than once.
B) Values appear in Table2 but NOT Table1.
C) Values appear in both tables more than once.
D) Values appear in Table more than once.
5. You have an Azure Databricks workspace that uses serverless compute.
You need to ingest data by using Lakeflow Jobs. New records must be processed as soon as they become available.
Which type of job trigger should you use for the ingestion?
A) continuous
B) manual
C) file arrival
D) scheduled
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: A |
By Elmer
