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NEW QUESTION: 1
Examine this query:
SELECT cust_name, amt_due
FROM customers
AS OF TIMESTAMP (SYSTIMESTAMP - INTERVAL '6' MINUTE)
WHERE cust_no = 'AYR2011';
Which two requirements guarantee that the query will execute successfully? (Choose two.)
A. Supplemental logging must be enabled.
B. Automatic Undo Management must be configured.
C. Undo retention guarantee must be enabled.
D. The database must be in ARCHIVELOG mode.
E. Row movement must be enabled for CUSTOMERS.
F. FLASHBACK must be ON for the database.
Answer: B,F
Explanation:
Explanation
Reference https://docs.oracle.com/cd/B12037_01/appdev.101/b10795/adfns_fl.htm

NEW QUESTION: 2
You are solving a classification task.
The dataset is imbalanced.
You need to select an Azure Machine Learning Studio module to improve the classification accuracy.
Which module should you use?
A. Fisher Linear Discriminant Analysis.
B. Permutation Feature Importance
C. Synthetic Minority Oversampling Technique (SMOTE)
D. Filter Based Feature Selection
Answer: C
Explanation:
Explanation
Use the SMOTE module in Azure Machine Learning Studio (classic) to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
You connect the SMOTE module to a dataset that is imbalanced. There are many reasons why a dataset might be imbalanced: the category you are targeting might be very rare in the population, or the data might simply be difficult to collect. Typically, you use SMOTE when the class you want to analyze is under-represented.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 3
At what granularity are blocks deduplicated on a Dell EMC PowerStore array?
A. 4 KB
B. 64 KB
C. 8 KB
D. 32 KB
Answer: C