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| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Engineer Associate Exam |
| Exam Number: | Databricks-Certified-Data-Engineer-Associate |
| Related Certifications: | Databricks Certified Data Analyst Associate Databricks Certified Data Engineer Professional |
| Passing Score: | Not publicly disclosed, approximately 70% |
| Exam Price: | 200 USD |
| Exam Duration: | 90 minutes |
| Available Languages: | Korean, English, Portuguese (Brazil), Japanese |
| Real Exam Qty: | 45 |
| Exam Format: | Multiple choice, Proctored |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Databricks Documentation Databricks Academy - Data Engineer Associate Learning Path |
| Exam Registration: | Official Registration |
| Sample Questions: | Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions |
| Exam Way: | Online proctored or in-person at authorized test centers |
| Pre Condition: | No mandatory prerequisites; 6+ months hands-on experience with Databricks and data engineering tasks recommended |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-associate |
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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.
NEW QUESTION # 296
A new data engineering team team. has been assigned to an ELT project. The new data engineering team will need full privileges on the database customers to fully manage the project.
Which of the following commands can be used to grant full permissions on the database to the new data engineering team?
Answer: C
Explanation:
Explanation
To grant full privileges on the database "customers" to the new data engineering team, you can use the GRANT ALL PRIVILEGES command as shown in option E. This command provides the team with all possible privileges on the specified database, allowing them to fully manage it.
NEW QUESTION # 297
Identify how the count_if function and the count where x is null can be used Consider a table random_values with below data.
What would be the output of below query?
select count_if(col > 1) as count_a. count(*) as count_b.count(col1) as count_c from random_values col1
0
1
2
NULL -
2
3
Answer: D
NEW QUESTION # 298
A data engineer is using Spark SQL to analyze a large dataset stored in Delta format. The engineer notices that queries filtering on partition columns run significantly faster. What is the primary reason for this performance improvement?
Answer: C
NEW QUESTION # 299
A data engineer is migrating pipeline tasks to reduce operational toil. The workspace uses Unity Catalog and is in a region that supports serverless. The engineer wants Databricks to auto-select instance types, manage scaling, apply Photon, and handle runtime upgrades automatically for job runs.
How should the data engineer meet this requirement while adhering to Databricks constraints?
Answer: D
Explanation:
Serverless compute for workflows is designed to minimize operational overhead for Databricks Jobs while enforcing Unity Catalog governance. When a job is configured to run on serverless compute (in supported regions), Databricks automatically selects instance types, manages autoscaling, enables Photon where applicable, and handles runtime upgrades without user intervention. This directly satisfies the requirement to reduce operational toil. All-purpose clusters (option B) and traditional job clusters (option C) still require users to manage cluster sizing, instance families, and runtime versions, which contradicts the goal of automation. SQL warehouses (option A) are intended for SQL workloads and do not support running general Python notebook job tasks as workflow steps. Databricks documentation specifies that serverless workflows are compatible with Unity Catalog and are the recommended approach when users want fully managed compute for scheduled pipelines and tasks, provided the workspace is in a supported region. This makes serverless compute the correct and fully compliant solution.
NEW QUESTION # 300
Which of the following describes a scenario in which a data team will want to utilize cluster pools?
Answer: A
Explanation:
Databricks cluster pools are a set of idle, ready-to-use instances that can reduce cluster start and auto-scaling times. This is useful for scenarios where a data team needs to run an automated report as quickly as possible, without waiting for the cluster to launch or scale up. Cluster pools can also help save costs by reusing idle instances across different clusters and avoiding DBU charges for idle instances in the pool. References: Best practices: pools | Databricks on AWS, Best practices: pools - Azure Databricks | Microsoft Learn, Best practices: pools | Databricks on Google Cloud
NEW QUESTION # 301
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