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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a highly sought-after certification in the field of data engineering. Databricks Certified Data Engineer Associate Exam certification is designed to validate the skills and knowledge required to design, build, and maintain data pipelines and data solutions on the Databricks platform. Databricks-Certified-Data-Engineer-Associate Exam is intended for professionals who have a strong understanding of data engineering concepts and have experience working with Databricks.
The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Exam is a certification exam that is designed for people who are interested in mastering the skills required for data engineering using the Databricks platform. Databricks Certified Data Engineer Associate Exam certification is globally recognized and is highly valued by employers since it proves that the certified individual has the knowledge and skills required to work with Databricks.
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Databricks Certified Data Engineer Associate Exam Sample Questions (Q32-Q37):
NEW QUESTION # 32
Which of the following is hosted completely in the control plane of the classic Databricks architecture?
Answer: C
Explanation:
Explanation
In the classic Databricks architecture, the control plane includes components like the Databricks web application, the Databricks REST API, and the Databricks Workspace. These components are responsible for managing and controlling the Databricks environment, including cluster provisioning, notebook management, access control, and job scheduling. The other options, such as worker nodes, JDBC data sources, Databricks Filesystem (DBFS), and driver nodes, are typically part of the data plane or the execution environment, which is separate from the control plane. Worker nodes are responsible for executing tasks and computations, JDBC data sources are used to connect to external databases, DBFS is a distributed file system for data storage, and driver nodes are responsible for coordinating the execution of Spark jobs.
NEW QUESTION # 33
A data engineer wants to create a new table containing the names of customers that live in France.
They have written the following command:
A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII).
Which of the following lines of code fills in the above blank to successfully complete the task?
Answer: B
Explanation:
In Databricks, when creating a table, you can add a comment to columns or the entire table to provide more information about the data it contains. In this case, since it's organization policy to indicate that the new table includes personally identifiable information (PII), option D is correct. The line of code would be added after defining the table structure and before closing with a semicolon. References: Data Engineer Associate Exam Guide, CREATE TABLE USING (Databricks SQL)
NEW QUESTION # 34
Which of the following data lakehouse features results in improved data quality over a traditional data lake?
Answer: B
Explanation:
A data lakehouse is a data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data12. One of the key features of a data lakehouse is that it supports ACID-compliant transactions, which means that it ensures data integrity, consistency, and isolation across concurrent read and write operations3. This feature results in improved data quality over a traditional data lake, which does not support transactions and may suffer from data corruption, duplication, or inconsistency due to concurrent or streaming data ingestion and processing . Reference: 1: What is a Data Lakehouse? - Databricks 2: What is a Data Lakehouse? Definition, features & benefits. - Qlik 3: ACID Transactions - Databricks : [Data Lake vs Data Warehouse: Key Differences] : [Data Lakehouse: The Future of Data Engineering]
NEW QUESTION # 35
Which two components function in the DB platform architecture's control plane? (Choose two.)
Answer: B,D
NEW QUESTION # 36
Which of the following describes the relationship between Gold tables and Silver tables?
Answer: B
Explanation:
According to the medallion lakehouse architecture, gold tables are the final layer of data that powers analytics, machine learning, and production applications. They are often highly refined and aggregated, containing data that has been transformed into knowledge, rather than just information. Silver tables, on the other hand, are the intermediate layer of data that represents a validated, enriched version of the raw data from the bronze layer. They provide an enterprise view of all its key business entities, concepts and transactions, but they may not have all the aggregations and calculations that are required for specific use cases. Therefore, gold tables are more likely to contain aggregations than silver tables. Reference:
What is the medallion lakehouse architecture?
What is a Medallion Architecture?
NEW QUESTION # 37
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