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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Ingestion and ELT Development	- Handling structured and semi-structured data - Data ingestion using Spark SQL and PySpark - ETL patterns and transformations
Topic 2: Databricks Lakehouse Platform Fundamentals	- Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage
Topic 3: Data Governance and Quality	- Data quality concepts and management - Data access control and governance - Unity Catalog basics
Topic 4: Data Processing and Transformations	- User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - Delta Lake fundamentals (tables, transactions, optimization) - PySpark DataFrame transformations
Topic 5: Productionizing Data Pipelines	- Scheduling and monitoring jobs - Pipeline deployment and operationalization - Databricks Workflows / Jobs orchestration

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Databricks-Certified-Data-Engineer-Associate Fragen Und Antworten - Databricks-Certified-Data-Engineer-Associate Zertifizierungsantworten

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Databricks Certified Data Engineer Associate Exam Databricks-Certified-Data-Engineer-Associate Prüfungsfragen mit Lösungen (Q208-Q213):

208. Frage
A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

A. They can reduce the cluster size of the SQL endpoint.
B. They can set up the dashboard's SQL endpoint to be serverless.
C. They can turn on the Auto Stop feature for the SQL endpoint.
D. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
E. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.

Antwort: C

209. Frage
A Python file is ready for production and the client wants to use the most efficient yet cost- effective type of cluster possible. The workload is quite small, only processing 10GBs of data with only simple joins and no complex aggregations or wide transformations.
Which cluster meets the requirement?

A. Job cluster with spot instances disabled
B. Interactive cluster
C. Job cluster with spot instances enabled
D. Job cluster with Photon enabled

Antwort: C

Begründung:
A job cluster is the most cost-effective option for production workloads because it is created only for the duration of the job and then terminated. Enabling spot instances further reduces cost, and the small, simple workload does not require advanced performance optimizations.

210. Frage
A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum?
Which of the following code blocks can the data engineer use to complete this task?

Antwort: A

Begründung:
https://www.w3schools.com/python/python_functions.asp
https://www.geeksforgeeks.org/python-functions/

211. Frage
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?

A. if day_of_week = 1 and review_period:
B. if day_of_week = 1 & review_period: = "True":
C. if day_of_week = 1 and review_period = "True":
D. if day_of_week == 1 and review_period:
E. if day_of_week == 1 and review_period == "True":

Antwort: D

Begründung:
In Python, the == operator is used to compare the values of two variables, while the = operator is used to assign a value to a variable. Therefore, option A and E are incorrect, as they use the = operator for comparison. Option B and C are also incorrect, as they compare the review_period variable to a string value "True", which is different from the boolean value True. Option D is the correct answer, as it uses the == operator to compare the day_of_week variable to the integer value 1, and the and operator to check if both conditions are true. If both conditions are true, then the final block of the Python program will be executed. References: [Python Operators], [Python If ... Else]

212. Frage
A data engineering team uses Declarative Automation Bundles (formerly Databricks Asset Bundles) to deploy the same codebase across dev, test, and prod environments. The team wants environment-specific behavior to be applied only through bundle configuration, without modifying notebooks, job definitions, or deployment logic during promotion. Which approach applies environment-specific configuration while meeting this requirement?

A. Parameterize environment-specific values inside notebooks and set those parameters when each job run is triggered.
B. Define bundle variables and reference them from bundle resources, then override variable values per environment using bundle targets.
C. Deploy the same bundle once and edit job settings in the workspace UI for each environment after deployment.
D. Use separate Git branches per environment so each branch can contain environment-specific configuration values.

Antwort: B

Begründung:
Bundle variables hold reusable configuration values, and bundle targets override those values for dev, test, and prod at deployment time. This preserves one codebase and avoids modifying notebooks or workspace resources during promotion.

213. Frage
......

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