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Databricks Certified Professional Data Engineer Exam Sample Questions (Q102-Q107):

NEW QUESTION # 102
Suppose there are three events then which formula must always be equal to P(E1|E2,E3)?

A. P(E1,E2;E3)/P(E2,E3)
B. P(E1,E2|E3)P(E3)
C. P(E1,E2,E3)P(E1)/P(E2:E3)
D. P(E1,E2|E3)P(E2|E3)P(E3)
E. P(E1,E2,E3)P(E2)P(E3)

Answer: A

Explanation:
Explanation
This is an application of conditional probability: P(E1,E2)=P(E1|E2)P(E2). so
P(E1|E2) = P(E1.E2)/P(E2)
P(E1,E2,E3)/P(E2,E3)
If the events are A and B respectively, this is said to be "the probability of A given B"
It is commonly denoted by P(A|B):or sometimes PB(A). In case that both "A" and "B" are categorical
variables, conditional probability table is typically used to represent the conditional probability.

NEW QUESTION # 103
The data science team has created and logged a production model using MLflow. The following code correctly imports and applies the production model to output the predictions as a new DataFrame namedpredswith the schema "customer_id LONG, predictions DOUBLE, date DATE".

The data science team would like predictions saved to a Delta Lake table with the ability to compare all predictions across time. Churn predictions will be made at most once per day.
Which code block accomplishes this task while minimizing potential compute costs?

A. preds.write.format("delta").save("/preds/churn_preds")
B.
C.
D. preds.write.mode("append").saveAsTable("churn_preds")
E.

Answer: D

NEW QUESTION # 104
A data engineer has ingested a JSON file into a table raw_table with the following schema:
1.transaction_id STRING,
2.payload ARRAY<customer_id:STRING, date:TIMESTAMP, store_id:STRING>
The data engineer wants to efficiently extract the date of each transaction into a table with the fol-lowing
schema:
1.transaction_id STRING,
2.date TIMESTAMP
Which of the following commands should the data engineer run to complete this task?

A. 1.SELECT transaction_id, payload[date]
2.FROM raw_table;
B. 1.SELECT transaction_id, payload.date
2.FROM raw_table;
C. 1.SELECT transaction_id, explode(payload)
2.FROM raw_table;
D. 1.SELECT transaction_id, date
2.FROM raw_table;
E. 1.SELECT transaction_id, date from payload
2.FROM raw_table;

Answer: B

NEW QUESTION # 105
The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. The recent_sensor_recordings table contains an identifying sensor_id alongside the timestamp and temperature for the most recent 5 minutes of recordings.
The below query is used to create the alert:

The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger when mean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute.
If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

A. The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query
B. The source query failed to update properly for three consecutive minutes and then restarted
C. The recent_sensor_recordingstable was unresponsive for three consecutive runs of the query
D. The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query
E. The total average temperature across all sensors exceeded 120 on three consecutive executions of the query

Answer: A

Explanation:
This is the correct answer because the query is using a GROUP BY clause on the sensor_id column, which means it will calculate the mean temperature for each sensor separately. The alert will trigger when the mean temperature for any sensor is greater than 120, which means at least one sensor had an average temperature above 120 for three consecutive minutes. The alert will stop when the mean temperature for all sensors drops below 120. Verified Reference: [Databricks Certified Data Engineer Professional], under "SQL Analytics" section; Databricks Documentation, under "Alerts" section.

NEW QUESTION # 106
You were asked to identify number of times a temperature sensor exceed threshold temperature (100.00) by each device, each row contains 5 readings collected every 5 minutes, fill in the blank with the appropriate functions.
Schema: deviceId INT, deviceTemp ARRAY<double>, dateTimeCollected TIMESTAMP

SELECT deviceId, __ (__ (__(deviceTemp], i -> i > 100.00)))
FROM devices
GROUP BY deviceId

A. SUM, SIZE, SLICE
B. SUM, SIZE, ARRAY_FILTER
C. SUM, COUNT, SIZE
D. SUM, SIZE, ARRAY_CONTAINS
E. SUM, SIZE, FILTER

Answer: E

Explanation:
Explanation
FILER function can be used to filter an array based on an expression
SIZE function can be used to get size of an array
SUM is used to calculate to total by device
Diagram Description automatically generated

NEW QUESTION # 107
......

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Updated Databricks Databricks-Certified-Professional-Data-Engineer Exam Questions - Fast Track To Get Success

Free PDF 2025 Useful Databricks-Certified-Professional-Data-Engineer: Databricks Certified Professional Data Engineer Exam Valid Vce

Databricks Certified Professional Data Engineer Exam Sample Questions (Q102-Q107):

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