Databricks-Certified-Data-Engineer-Associate Latest Exam - Databricks-Certified-Data-Engineer-Associate Relevant Answers

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The Databricks Databricks-Certified-Data-Engineer-Associate Exam covers a range of topics, including data ingestion, processing, and storage. Candidates are tested on their ability to design and implement data pipelines, data models, and data processing workflows using Databricks. Databricks is a cloud-based data platform that provides a unified analytics platform for data engineering, data science, and machine learning.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague of the data engineer informs them that changes have been made and synced to the central Git repository. The data engineer now needs to sync their Databricks Repo to get the changes from the central Git repository.
Which of the following Git operations does the data engineer need to run to accomplish this task?

A. Commit
B. Pull
C. Push
D. Clone
E. Merge

Answer: B

Explanation:
To sync a Databricks Repo with the changes from a central Git repository, the data engineer needs to run the Git pull operation. This operation fetches the latest updates from the remote repository and merges them with the local repository. The data engineer can use the Pull button in the Databricks Repos UI, or use the git pull command in a terminal session. The other options are not relevant for this task, as they either push changes to the remote repository (Push), combine two branches (Merge), save changes to the local repository (Commit), or create a new local repository from a remote one (Clone). Reference:
Run Git operations on Databricks Repos
Git pull

NEW QUESTION # 21
Which of the following describes the relationship between Bronze tables and raw data?

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

Answer: B

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 # 22
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Answer: B

Explanation:
https://www.databricks.com/blog/2021/10/20/introducing-sql-user-defined-functions.html

NEW QUESTION # 23
A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.
Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?

A. They can use jobs clusters instead of all-purpose clusters
B. They can configure the clusters to be single-node
C. They can use endpoints available in Databricks SQL
D. They can use clusters that are from a cluster pool
E. They can configure the clusters to autoscale for larger data sizes

Answer: D

Explanation:
The best action that the data engineer can perform to improve the start up time for the clusters used for the Job is to use clusters that are from a cluster pool. A cluster pool is a set of idle clusters that can be used by jobs or interactive sessions. By using a cluster pool, the data engineer can avoid the cluster creation time and reduce the latency of the tasks. Cluster pools also offer cost savings and resource efficiency, as they can be shared by multiple users and jobs.
Option A is not relevant, as endpoints available in Databricks SQL are used for creating and managing SQL analytics workloads, not for improving cluster start up time.
Option B is not correct, as jobs clusters and all-purpose clusters have similar start up times. Jobs clusters are clusters that are dedicated to run a single job and are terminated when the job is completed. All-purpose clusters are clusters that can be used for multiple purposes, such as interactive sessions, notebooks, or multiple jobs. Both types of clusters can benefit from using a cluster pool.
Option C is not advisable, as configuring the clusters to be single-node will reduce the parallelism and performance of the tasks. Single-node clusters are clusters that have only one worker node and are typically used for testing or development purposes. They are not suitable for running production jobs that require high scalability and fault tolerance.
Option E is not helpful, as configuring the clusters to autoscale for larger data sizes will not affect the start up time of the clusters. Autoscaling is a feature that allows clusters to dynamically adjust the number of worker nodes based on the workload. It can help optimize the resource utilization and cost efficiency of the clusters, but it does not speed up the cluster creation process.
Reference:
Cluster Pools
Jobs
Clusters
[Databricks Data Engineer Professional Exam Guide]

NEW QUESTION # 24
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 CREATE ON DATABASE team TO customers;
C. GRANT CREATE ON DATABASE customers TO team;
D. GRANT VIEW ON CATALOG customers TO team;
E. GRANT USAGE ON CATALOG team TO customers;

Answer: A

NEW QUESTION # 25
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DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE LATEST EXAM - DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE RELEVANT ANSWERS

Databricks-Certified-Data-Engineer-Associate Latest Exam - Databricks-Certified-Data-Engineer-Associate Relevant Answers