VCE DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE FORMAT | 100% FREE RELIABLE DEMO DATABRICKS CERTIFIED DATA ENGINEER ASSOCIATE EXAM TEST

Vce Databricks-Certified-Data-Engineer-Associate Format | 100% Free Reliable Demo Databricks Certified Data Engineer Associate Exam Test

Vce Databricks-Certified-Data-Engineer-Associate Format | 100% Free Reliable Demo Databricks Certified Data Engineer Associate Exam Test

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To become a Databricks-Certified-Data-Engineer-Associate, candidates must pass a rigorous exam that tests their understanding of Databricks and its various components. Databricks-Certified-Data-Engineer-Associate Exam consists of multiple-choice questions and requires candidates to demonstrate their knowledge of data engineering best practices, data processing techniques, and machine learning algorithms. Successful candidates will receive a certification that recognizes their expertise in working with Databricks.

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Databricks Certified Data Engineer Associate Exam is a vendor-neutral certification that tests candidates on their understanding of Databricks architecture and features, data ingestion and processing, data transformation and storage, and machine learning. Databricks-Certified-Data-Engineer-Associate exam also covers important concepts such as performance tuning, security, and troubleshooting in Databricks. Passing the exam demonstrates that a candidate has the skills, knowledge, and expertise to work with Databricks to design, build, and maintain advanced data pipelines and solutions.

The Databricks Certified Data Engineer Associate Exam certification exam consists of 60 multiple-choice questions that need to be answered within 90 minutes. Databricks-Certified-Data-Engineer-Associate Exam is available in English and is delivered online through the GAQM testing platform. Databricks Certified Data Engineer Associate Exam certification exam is open to all individuals who are interested in data engineering and Databricks, regardless of their educational background.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q87-Q92):

NEW QUESTION # 87
A data engineer needs to apply custom logic to identify employees with more than 5 years of experience in array column employees in table stores. The custom logic should create a new column exp_employees that is an array of all of the employees with more than 5 years of experience for each row. In order to apply this custom logic at scale, the data engineer wants to use the FILTER higher-order function.
Which of the following code blocks successfully completes this task?

  • A. Option D
  • B. Option A
  • C. Option E
  • D. Option B
  • E. Option C

Answer: B


NEW QUESTION # 88
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The cade block used by the data engineer is below:

If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?

  • A. trigger()
  • B. trigger("5 seconds")
  • C. trigger(once="5 seconds")
  • D. trigger(continuous="5 seconds")
  • E. trigger(processingTime="5 seconds")

Answer: E

Explanation:
Explanation
# ProcessingTime trigger with two-seconds micro-batch interval
df.writeStream
format("console")
trigger(processingTime='2 seconds')
start()
https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#triggers


NEW QUESTION # 89
Which of the following benefits is provided by the array functions from Spark SQL?

  • A. An ability to work with complex, nested data ingested from JSON files
  • B. An ability to work with time-related data in specified intervals
  • C. An ability to work with data in a variety of types at once
  • D. An ability to work with an array of tables for procedural automation
  • E. An ability to work with data within certain partitions and windows

Answer: E


NEW QUESTION # 90
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

  • A. None of these
  • B. Data warehouse
  • C. Data lake
  • D. Data lakehouse
  • E. All of these

Answer: D

Explanation:
A data lakehouse is a new paradigm that can be used to simplify and unify siloed data architectures that are specialized for specific use cases. A data lakehouse combines the best of both data lakes and data warehouses, providing a single platform that supports diverse data types, open standards, low-cost storage, high-performance queries, ACID transactions, schema enforcement, and governance. A data lakehouse enables data engineers to build reliable and scalable data pipelines that can serve various downstream applications and users, such as data science, machine learning, analytics, and reporting. A data lakehouse leverages the power of Delta Lake, a storage layer that brings reliability and performance to data lakes. Reference: What is a data lakehouse?, Delta Lake, Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics


NEW QUESTION # 91
Which of the following is stored in the Databricks customer's cloud account?

  • A. Databricks web application
  • B. Repos
  • C. Data
  • D. Notebooks
  • E. Cluster management metadata

Answer: C

Explanation:
The only option that is stored in the Databricks customer's cloud account is data. Data is stored in the customer's cloud storage service, such as AWS S3 or Azure Data Lake Storage. The customer has full control and ownership of their data and can access it directly from their cloud account.
Option A is not correct, as the Databricks web application is hosted and managed by Databricks on their own cloud infrastructure. The customer does not need to install or maintain the web application, but only needs to access it through a web browser.
Option B is not correct, as the cluster management metadata is stored and managed by Databricks on their own cloud infrastructure. The cluster management metadata includes information such as cluster configuration, status, logs, and metrics. The customer can view and manage their clusters through the Databricks web application, but does not have direct access to the cluster management metadata.
Option C is not correct, as the repos are stored and managed by Databricks on their own cloud infrastructure. Repos are version-controlled repositories that store code and data files for Databricks projects. The customer can create and manage their repos through the Databricks web application, but does not have direct access to the repos.
Option E is not correct, as the notebooks are stored and managed by Databricks on their own cloud infrastructure. Notebooks are interactive documents that contain code, text, and visualizations for Databricks workflows. The customer can create and manage their notebooks through the Databricks web application, but does not have direct access to the notebooks.
Reference:
Databricks Architecture
Databricks Data Sources
Databricks Repos
[Databricks Notebooks]
[Databricks Data Engineer Professional Exam Guide]


NEW QUESTION # 92
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