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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

Section	Objectives
Databricks Lakehouse Platform Fundamentals	- Clusters, notebooks, and basic Databricks environment usage - Workspace, architecture, and core platform concepts
Data Processing and Transformations	- User-defined functions (UDFs) - Delta Lake fundamentals (tables, transactions, optimization) - PySpark DataFrame transformations - Apache Spark SQL operations (joins, aggregations, filtering)
Productionizing Data Pipelines	- Databricks Workflows / Jobs orchestration - Scheduling and monitoring jobs - Pipeline deployment and operationalization
Data Governance and Quality	- Unity Catalog basics - Data quality concepts and management - Data access control and governance
Data Ingestion and ELT Development	- Handling structured and semi-structured data - ETL patterns and transformations - Data ingestion using Spark SQL and PySpark

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q32-Q37):

NEW QUESTION # 32
A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos.
Which of the following is an advantage of using Databricks Repos over the Databricks Notebooks versioning?

A. Databricks Repos allows users to revert to previous versions of a notebook
B. Databricks Repos provides the ability to comment on specific changes
C. Databricks Repos automatically saves development progress
D. Databricks Repos supports the use of multiple branches
E. Databricks Repos is wholly housed within the Databricks Lakehouse Platform

Answer: D

Explanation:
Explanation
An advantage of using Databricks Repos over the built-in Databricks Notebooks versioning is the ability to work with multiple branches. Branching is a fundamental feature ofversion control systems like Git, which Databricks Repos is built upon. It allows you to create separate branches for different tasks, features, or experiments within your project. This separation helps in parallel development and experimentation without affecting the main branch or the work of other team members. Branching provides a more organized and collaborative development environment, making it easier to merge changes and manage different development efforts. While Databricks Notebooks versioning also allows you to track versions of notebooks, it may not provide the same level of flexibility and collaboration as branching in Databricks Repos.

NEW QUESTION # 33
A data engineer is cleaning a Bronze table that receives the same customer records from multiple source systems. Duplicate rows have the same customer_id and email values but different ingestion_timestamp values. The Silver table should contain only one record for each unique combination of customer_id and email.
Which PySpark operation correctly deduplicates the records based on the business keys?

A. df.groupBy("customer_id", "email").agg(max("ingestion_timestamp").alias("latest_ts"))
B. df.select("customer_id", "email").distinct()
C. df.dropDuplicates(["customer_id", "email"])
D. df.distinct()

Answer: C

NEW QUESTION # 34
A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:

After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?

A. The PARQUET file format does not support COPY INTO.
B. The previous day's file has already been copied into the table.
C. The names of the files to be copied were not included with the FILES keyword.
D. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
E. The COPY INTO statement requires the table to be refreshed to view the copied rows.

Answer: B

Explanation:
The COPY INTO statement is an idempotent operation, which means that it will skip any files that have already been loaded into the target table1. This ensures that the data is not duplicated or corrupted by multiple attempts to load the same file. Therefore, if the data engineer runs the same command every day without specifying the names of the files to be copied with the FILES keyword or a glob pattern with the PATTERN keyword, the statement will only copy the first file that matches the source location and ignore the rest. To avoid this problem, the data engineer should either use the FILES or PATTERN keywords to filter the files to be copied based on the date or some other criteria, or delete the files from the source location after they are copied into the table2. References: 1: COPY INTO | Databricks on AWS 2: Get started using COPY INTO to load data | Databricks on AWS

NEW QUESTION # 35
A new data engineering team team. has been assigned to an ELT project. The new data engineering team will need full privileges on the database customers to fully manage the project.
Which of the following commands can be used to grant full permissions on the database to the new data engineering team?

A. GRANT ALL PRIVILEGES ON DATABASE customers TO team;
B. GRANT USAGE ON DATABASE customers TO team;
C. GRANT ALL PRIVILEGES ON DATABASE team TO customers;
D. GRANT SELECT CREATE MODIFY USAGE PRIVILEGES ON DATABASE customers TO team;
E. GRANT SELECT PRIVILEGES ON DATABASE customers TO teams;

Answer: A

Explanation:
To grant full permissions on a database to a user, group, or service principal, the GRANT ALL PRIVILEGES ON DATABASE command can be used. This command grants all the applicable privileges on the database, such as CREATE, SELECT, MODIFY, and USAGE. The other options are either incorrect or incomplete, as they do not grant all the privileges or specify the wrong database or principal. Reference:
GRANT
Privileges

NEW QUESTION # 36
A data engineer needs to use a Delta table as part of a data pipeline, but they do not know if they have the appropriate permissions.
In which location can the data engineer review their permissions on the table?

A. Dashboards
B. Catalog Explorer
C. Jobs
D. Repos

Answer: B

NEW QUESTION # 37
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