File Info
| Exam | Microsoft Azure Data Fundamentals |
| Number | DP-900 |
| File Name | Microsoft.DP-900.NewDumps.2021-07-30.112q.tqb |
| Size | 6 MB |
| Posted | Jul 30, 2021 |
| Download | Microsoft.DP-900.NewDumps.2021-07-30.112q.tqb |
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Demo Questions
Question 1
To complete the sentence, select the appropriate option in the answer area.
Correct answer: To work with this question, an Exam Simulator is required.
Explanation:
Reference:https://demand-planning.com/2020/01/20/the-differences-between-descriptive-diagnostic-predictivecognitive-analytics/ Reference:
https://demand-planning.com/2020/01/20/the-differences-between-descriptive-diagnostic-predictivecognitive-analytics/
Question 2
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct answer: To work with this question, an Exam Simulator is required.
Explanation:
Reference:https://www.sqlshack.com/what-is-database-normalization-in-sql-server/ Reference:
https://www.sqlshack.com/what-is-database-normalization-in-sql-server/
Question 3
To complete the sentence, select the appropriate option in the answer area.
Correct answer: To work with this question, an Exam Simulator is required.
Explanation:
In the ELT pipeline, the transformation occurs in the target data store. ELT only works well when the target system is powerful enough to transform the data efficiently.Incorrect Answers:The data does not need to be fully processed: Often, the three ETL phases are run in parallel to save time.For example, while data is being extracted, a transformation process could be working on data already received and prepare it for loading, and a loading process can begin working on the prepared data, rather than waiting for the entire extraction process to complete.The target does need to be a relational database.Reference:https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl In the ELT pipeline, the transformation occurs in the target data store. ELT only works well when the target system is powerful enough to transform the data efficiently.
Incorrect Answers:
The data does not need to be fully processed: Often, the three ETL phases are run in parallel to save time.
For example, while data is being extracted, a transformation process could be working on data already received and prepare it for loading, and a loading process can begin working on the prepared data, rather than waiting for the entire extraction process to complete.
The target does need to be a relational database.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl
