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

Section	Objectives
Topic 1: Databricks Lakehouse Platform Fundamentals	- Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage
Topic 2: Productionizing Data Pipelines	- Databricks Workflows / Jobs orchestration - Scheduling and monitoring jobs - Pipeline deployment and operationalization
Topic 3: Data Ingestion and ELT Development	- Data ingestion using Spark SQL and PySpark - ETL patterns and transformations - Handling structured and semi-structured data
Topic 4: Data Governance and Quality	- Data quality concepts and management - Unity Catalog basics - Data access control and governance
Topic 5: Data Processing and Transformations	- PySpark DataFrame transformations - Apache Spark SQL operations (joins, aggregations, filtering) - User-defined functions (UDFs) - Delta Lake fundamentals (tables, transactions, optimization)

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q212-Q217):

NEW QUESTION # 212
Identify a scenario to use an external table.
A Data Engineer needs to create a parquet bronze table and wants to ensure that it gets stored in a specific path in an external location.
Which table can be created in this scenario?

A. A managed table where the catalog has managed location pointing to specific path in external location.
B. An external table where the location is pointing to specific path in external location.
C. An external table where the schema has managed location pointing to specific path in external location.
D. A managed table where the location is pointing to specific path in external location.

Answer: B

NEW QUESTION # 213
A Data Engineer is designing Bronze layer in Databricks Medallion Architecture. The raw data is collected from multiple sources (Clickstream in JSON, Transactions in CSV).
The task is to design the Bronze layer of the Medallion Architecture to ingest and store this raw data for further processing.
Which operation applies to the Bronze layer?

A. Aggregate and transform source data to calculate daily sales performance metrics.
B. Apply complex business logic to enrich raw data with customer segmentation labels.
C. Clean and standardize raw data by removing null values and enforcing schemas.
D. Ingest raw data without transformations, preserving original schemas, and store in Delta format.

Answer: D

Explanation:
In the Bronze layer of the Medallion Architecture, raw data from multiple sources is ingested without transformations while preserving its original schema. The data is then stored in Delta format, serving as the single source of truth for downstream Silver and Gold layers where cleaning, standardization, and business logic are applied.

NEW QUESTION # 214
An organization plans to share a large dataset stored in a Databricks workspace on AWS with a partner organization whose Databricks workspace is hosted on Azure. The data engineer wants to minimize data transfer costs while ensuring secure and efficient data sharing. Which strategy will reduce data egress costs associated with cross-cloud data sharing?

A. Configure VPN connection between AWS and Azure for faster data sharing
B. Migrating the dataset to Cloudflare R2 object storage before sharing
C. Sharing data via pre-signed URLs without monitoring egress costs
D. Using Delta Sharing without any additional configurations

Answer: D

Explanation:
Delta Sharing natively supports cross-cloud data access without requiring data duplication or special networking setups. It allows secure sharing of datasets across different cloud providers while minimizing egress costs, since recipients query the data directly from its source location rather than transferring large volumes unnecessarily.

NEW QUESTION # 215
A data engineer wants to ensure that duplicate records are removed from a dataset based on specific columns before writing to a Delta table. Which Spark DataFrame method removes duplicate rows?

A. dropDuplicates
B. uniqueRows
C. distinctBy
D. removeDuplicates

Answer: A

NEW QUESTION # 216
A new data engineering team has been assigned to work on a project. The team will need access to database customers in order to see what tables already exist. The team has its own group team.
Which of the following commands can be used to grant the necessary permission on the entire database to the new team?

A. GRANT CREATE ON DATABASE customers TO team;
B. GRANT USAGE ON CATALOG team TO customers;
C. GRANT USAGE ON DATABASE customers TO team;
D. GRANT VIEW ON CATALOG customers TO team;
E. GRANT CREATE ON DATABASE team TO customers;

Answer: C

Explanation:
Explanation
The GRANT statement is used to grant privileges on a database, table, or view to a user or role. The ALL PRIVILEGES option grants all possible privileges on the specified object, such as CREATE, SELECT, MODIFY, and USAGE. The syntax of the GRANT statement is:
GRANT privilege_type ON object TO user_or_role;
Therefore, to grant full permissions on the database customers to the new data engineering team, the command should be:
GRANT ALL PRIVILEGES ON DATABASE customers TO team;

NEW QUESTION # 217
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