VALID AND RELIABLE DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE EXAM QUESTIONS [2025]

Valid and Reliable Databricks-Certified-Data-Engineer-Associate Exam Questions [2025]

Valid and Reliable Databricks-Certified-Data-Engineer-Associate Exam Questions [2025]

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The Databricks Databricks-Certified-Data-Engineer-Associate Exam consists of 60 multiple-choice questions and is designed to test your understanding of Databricks concepts, including data engineering, data processing, data storage, and data analysis. To pass the exam, you must score at least 70%. Databricks-Certified-Data-Engineer-Associate exam can be taken online and is available in several languages, including English, Spanish, and Chinese. Upon passing the exam, you will receive a Databricks Certified Data Engineer Associate certification, which is recognized globally as a mark of expertise in big data processing using Databricks.

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Databricks-Certified-Data-Engineer-Associate Exam Quizzes - Valid Databricks-Certified-Data-Engineer-Associate Test Questions

The Databricks-Certified-Data-Engineer-Associate exam requires the candidates to have thorough understanding on the syllabus contents as well as practical exposure of various concepts of certification. Obviously such a syllabus demands comprehensive studies and experience. If you are lack of these skills, you should find our Databricks-Certified-Data-Engineer-Associate study questions to help you equip yourself well. As long as you study with our Databricks-Certified-Data-Engineer-Associate practice engine, you will find they can help you get the best percentage on your way to success.

The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Exam is a certification that is designed to test the skills and knowledge of data engineers who work with Databricks. Data engineers play a critical role in any organization that relies on data to make decisions. They are responsible for the design, construction, and maintenance of data pipelines, data models, and data warehouses.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q109-Q114):

NEW QUESTION # 109
Which of the following describes the relationship between Gold tables and Silver tables?

  • A. Gold tables are more likely to contain a less refined view of data than Silver tables.
  • B. Gold tables are more likely to contain valuable data than Silver tables.
  • C. Gold tables are more likely to contain more data than Silver tables.
  • D. Gold tables are more likely to contain truthful data than Silver tables.
  • E. Gold tables are more likely to contain aggregations than Silver tables.

Answer: E

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 # 110
A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.
Which of the following approaches can the data engineer use to set up the new task?

  • A. They can create a new task in the existing Job and then add it as a dependency of the original task.
  • B. They can create a new job from scratch and add both tasks to run concurrently.
  • C. They can clone the existing task to a new Job and then edit it to run the new notebook.
  • D. They can create a new task in the existing Job and then add the original task as a dependency of the new task.
  • E. They can clone the existing task in the existing Job and update it to run the new notebook.

Answer: A

Explanation:
To set up the new task to run a new notebook prior to the original task in a single-task Job, the data engineer can use the following approach: In the existing Job, create a new task that corresponds to the new notebook that needs to be run. Set up the new task with the appropriate configuration, specifying the notebook to be executed and any necessary parameters or dependencies. Once the new task is created, designate it as a dependency of the original task in the Job configuration. This ensures that the new task is executed before the original task.


NEW QUESTION # 111
Which of the following describes the relationship between Bronze tables and raw data?

  • A. Bronze tables contain more truthful data than raw data.
  • B. Bronze tables contain a less refined view of data than raw data.
  • C. Bronze tables contain aggregates while raw data is unaggregated.
  • D. Bronze tables contain less data than raw data files.
  • E. Bronze tables contain raw data with a schema applied.

Answer: E

Explanation:
Bronze tables are the first layer of a medallion architecture, which is a data design pattern used to organize data in a lakehouse. Bronze tables contain raw data ingested from various sources, such as RDBMS data, JSON files, IoT data, etc. The table structures in this layer correspond to the source system table structures "as-is", along with any additional metadata columns that capture the load date/time, process ID, etc. The only transformation applied to the raw data in this layer is to apply a schema, which defines the column names and data types of the table. The schema can be inferred from the data source or specified explicitly. Applying a schema to the raw data enables the use of SQL and other structured query languages to access and analyze the data. Therefore, option E is the correct answer. Reference: What is a Medallion Architecture?, Raw Data Ingestion into Delta Lake Bronze tables using Azure Synapse Mapping Data Flow, Apache Spark + Delta Lake concepts, Delta Lake Architecture & Azure Databricks Workspace.


NEW QUESTION # 112
A data engineer has joined an existing project and they see the following query in the project repository:
CREATE STREAMING LIVE TABLE loyal_customers AS
SELECT customer_id -
FROM STREAM(LIVE.customers)
WHERE loyalty_level = 'high';
Which of the following describes why the STREAM function is included in the query?

  • A. The data in the customers table has been updated since its last run.
  • B. The table being created is a live table.
  • C. The customers table is a streaming live table.
  • D. The customers table is a reference to a Structured Streaming query on a PySpark DataFrame.
  • E. The STREAM function is not needed and will cause an error.

Answer: C

Explanation:
The STREAM function is used to process data from a streaming live table or view, which is a table or view that contains data that has been added only since the last pipeline update. Streaming live tables and views are stateful, meaning that they retain the state of the previous pipeline run and only process new data based on the current query. This is useful for incremental processing of streaming or batch data sources. The customers table in the query is a streaming live table, which means that it contains the latest data from the source. The STREAM function enables the query to read the data from the customers table incrementally and create another streaming live table named loyal_customers, which contains the customer IDs of the customers with high loyalty level. References: Difference between LIVE TABLE and STREAMING LIVE TABLE, CREATE STREAMING TABLE, Load data using streaming tables in Databricks SQL.


NEW QUESTION # 113
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 USAGE ON DATABASE customers TO team;
  • B. GRANT USAGE ON CATALOG team TO customers;
  • C. GRANT CREATE ON DATABASE customers TO team;
  • D. GRANT VIEW ON CATALOG customers TO team;
  • E. GRANT CREATE ON DATABASE team TO customers;

Answer: A

Explanation:
The correct command to grant the necessary permission on the entire database to the new team is to use the GRANT USAGE command. The GRANT USAGE command grants the principal the ability to access the securable object, such as a database, schema, or table. In this case, the securable object is the database customers, and the principal is the group team. By granting usage on the database, the team will be able to see what tables already exist in the database. Option E is the only option that uses the correct syntax and the correct privilege type for this scenario. Option A uses the wrong privilege type (VIEW) and the wrong securable object (CATALOG). Option B uses the wrong privilege type (CREATE), which would allow the team to create new tables in the database, but not necessarily see the existing ones. Option C uses the wrong securable object (CATALOG) and the wrong principal (customers). Option D uses the wrong securable object (team) and the wrong principal (customers). Reference: GRANT, Privilege types, Securable objects, Principals


NEW QUESTION # 114
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