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

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

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q170-Q175):

NEW QUESTION # 170
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 clone the existing task to a new Job and then edit it to run the new notebook.
B. They can clone the existing task in the existing Job and update it to run the new notebook.
C. They can create a new task in the existing Job and then add it as a dependency of the original task.
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 create a new job from scratch and add both tasks to run concurrently.

Answer: C

Explanation:
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 # 171
A data engineer has written a function in a Databricks Notebook to calculate the population of bacteria in a given medium.

Analysts use this function in the notebook and sometimes provide input arguments of the wrong data type, which can cause errors during execution.
Which Databricks feature will help the data engineer quickly identify if an incorrect data type has been provided as input?

A. The Spark User interface has a debug tab that contains the variables that are used in this session.
B. The Databricks debugger enables breakpoints that will raise an error if the wrong data type is submitted
C. The Data Engineer should add print statements to find out what the variable is.
D. The Databricks debugger enables the use of a variable explorer to see at a glance the value of the variables.

Answer: D

NEW QUESTION # 172
A data engineer has been given a new record of data:
id STRING = 'a1'
rank INTEGER = 6
rating FLOAT = 9.4
Which of the following SQL commands can be used to append the new record to an existing Delta table my_table?

A. UPDATE VALUES ('a1', 6, 9.4) my_table
B. INSERT VALUES ( 'a1' , 6, 9.4) INTO my_table
C. my_table UNION VALUES ('a1', 6, 9.4)
D. INSERT INTO my_table VALUES ('a1', 6, 9.4)
E. UPDATE my_table VALUES ('a1', 6, 9.4)

Answer: D

Explanation:
To append a new record to an existing Delta table, you can use the INSERT INTO statement with the VALUES clause. This statement will insert one or more rows into the table with the specified values. Option A is the only code block that follows this syntax correctly. Option B is incorrect, as it uses the UNION operator, which will return a new table that is the union of two tables, not append to an existing table. Option C is incorrect, as it uses the INSERT VALUES statement, which is not a valid SQL syntax. Option D is incorrect, as it uses the UPDATE statement, which will modify existing rows in the table, not append new rows. Option E is incorrect, as it uses the UPDATE VALUES statement, which is also not a valid SQL syntax. Reference: Insert data into a table using SQL | Databricks on AWS, Insert data into a table using SQL - Azure Databricks, Delta Lake Quickstart - Azure Databricks

NEW QUESTION # 173
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?

A. They can set up an Alert with one-time notifications.
B. They can set up an Alert without notifications.
C. They can set up an Alert with a new webhook alert destination.
D. They can set up an Alert with a new email alert destination.
E. They can set up an Alert with a custom template.

Answer: C

Explanation:
A webhook alert destination is a notification destination that allows Databricks to send HTTP POST requests to a third-party endpoint when an alert is triggered. This enables the data engineer to integrate Databricks alerts with their preferred messaging or collaboration platform, such as Slack, Microsoft Teams, or PagerDuty. To set up a webhook alert destination, the data engineer needs to create and configure a webhook connector in their messaging platform, and then add the webhook URL to the Databricks notification destination. After that, the data engineer can create an alert for their Databricks SQL query, and select the webhook alert destination as the notification destination. The alert can be configured with a custom condition, such as when the number of stores with $0 in sales is greater than zero, and a custom message template, such as "Alert: {number_of_stores} stores have $0 in sales". The alert can also be configured with a recurrence interval, such as every hour, to check the query result periodically. When the alert condition is met, the data engineer and their team will receive a notification via the messaging webhook, with the custom message and a link to the Databricks SQL query. The other options are either not suitable for sending notifications via a messaging webhook (A, B, E), or not suitable for sending recurring notifications ©. References: Databricks Documentation - Manage notification destinations, Databricks Documentation - Create alerts for Databricks SQL queries, Databricks Documentation - Configure alert conditions and messages.

NEW QUESTION # 174
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

A. CREATE TABLE all_transactions ASSELECT * FROM march_transactionsUNION SELECT * FROM april_transactions;
B. CREATE TABLE all_transactions ASSELECT * FROM march_transactionsOUTER JOIN SELECT * FROM april_transactions;
C. CREATE TABLE all_transactions ASSELECT * FROM march_transactionsMERGE SELECT * FROM april_transactions;
D. CREATE TABLE all_transactions ASSELECT * FROM march_transactionsINNER JOIN SELECT * FROM april_transactions;
E. CREATE TABLE all_transactions ASSELECT * FROM march_transactionsINTERSECT SELECT * from april_transactions;

Answer: A

Explanation:
The correct command to create a new table that contains all records from two tables without duplicate records is to use the UNION operator. The UNION operator combines the results of two queries and removes any duplicate rows. The INNER JOIN, OUTER JOIN, and MERGE operators do not remove duplicate rows, and the INTERSECT operator only returns the rows that are common to both tables. Therefore, option B is the only correct answer. Reference: Databricks SQL Reference - UNION, Databricks SQL Reference - JOIN, Databricks SQL Reference - MERGE, [Databricks SQL Reference - INTERSECT]

NEW QUESTION # 175
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