Microsoft DP-750 : Implementing Data Engineering Solutions Using Azure Databricks

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Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains two catalogs named Catalog1 and Catalog2.
An external application uses a service principal named SP1 to connect to a SQL warehouse.
You need to ensure that SP1 can query the data in Catalog1 and Catalog2. The solution must follow the principle of least privilege.
Which permissions should you grant to SP1 for the catalogs?

A) USE CATALOG, USE SCHEMA, and SELECT
B) USE SCHEMA and SELECT
C) USE CATALOG and SELECT
D) USE CATALOG and USE SCHEMA

2. 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 Column1. Table2 contains a column named Column2.
You run the following query.
SELECT Colum1
FROM Table1
GROUP BY Column1
HAVING COUNT(*) > 1
INTERSECT
SELECT Column2
FROM Table2
GROUP BY Column2
HAVING COUNT(*) > 1;
What occurs when you run the query?

A) Values appear in Table1 more than once.
B) Values appear in either table more than once.
C) Values appear in both tables more than once.
D) Values appear in Table2 but NOT Table1.

3. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You plan to ingest data from CSV files stored in Azure Data Lake Storage Gen2. New rows are appended frequently.
You need to implement a data ingestion solution that meets the following requirements:
- New data must be available in near-real-time (NRT).
- The data must be stored in managed Delta tables.
- The solution must minimize custom code and maintenance effort.
What should you include in the solution?

A) Auto Loader
B) scheduled Apache Spark batch jobs
C) an Azure Data Factory pipeline
D) an external table that references the CSV files

4. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named Catalog1. Catalog1 contains a table named Transactions. Transactions contains the following columns:
- transaction_id
- customer_name
- email_address
- credit_card_number
- transaction_amount
You need to ensure that business analysts can query all the rows in the Transactions table. The solution must meet the following requirements:
- Prevent the analysts from seeing the full values in the email_address and credit_card_number columns.
- Ensure that the analysts can see only the values after the @
character in each email address.
- Ensure that the analysts can see only the last four digits of each
credit card number.
- Enable the analysts to query the table without errors.
- Follow the principle of least privilege.
What should you do?

A) Grant the analysts the SELECTpermission for the Transactions table and implement row-level filters.
B) Grant the analysts the SELECTpermission for the Transactions table and apply column-level encryption.
C) Grant the analysts the SELECT permission for the Transactions table and apply column masks to email_address and credit_card_number.
D) Grant the analysts the SELECT permission for columns that do NOT contain sensitive data.

5. Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named catalog1.
You have a group named group1.
You plan to create a schema named schema1 in catalog1.
You need to ensure that group1 meets the following requirements:
- Can create tables in schema1
- Can modify and query tables
- Cannot grant permissions for the schema and its objects
How should you complete the SQL statements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solutions: