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NEW QUESTION: 1
What is the effect of setting the STATISTICS_LEVEL initialization parameter to BASIC?
A. Only timed operating system (OS) statistics and plan execution statistics are collected.
B. The Oracle server dynamically generates the necessary object-level statistics on tables as part of query optimization.
C. Automatic Workload Repository (AWR) snapshots are not generated automatically.
D. Optimizer statistics are collected automatically.
Answer: C
Explanation:
References: https://docs.oracle.com/cd/B28359_01/server.111/b28320/initparams240.htm#REFRN10214

NEW QUESTION: 2
Examine this code:

What will be the outcome with SERVEROUTPUT enabled?
A. LENGTH : 100.13 EXTRA_LEN : 15.25 TOTAL LENGTH : 115.38
B. LENGTH : 100.1254 EXTRA_LEN : 15.25 TOTAL LENGTH : 115.38
C. LENGTH : 100.1254 EXTRA_LEN : 15.25
TOTAL LENGTH : 115.3754
D. The PL/SQL block will fail with a runtime exception.
E. LENGTH : 100.1254 EXTRA_LEN : 15.247 TOTAL LENGTH : 115.37
Answer: D

NEW QUESTION: 3
A Data Engineer needs to build a model using a dataset containing customer credit card information.
How can the Data Engineer ensure the data remains encrypted and the credit card information is secure?
A. Use an Amazon SageMaker launch configuration to encrypt the data once it is copied to the SageMaker instance in a VPC Use the SageMaker principal component analysis (PCA) algorithm to reduce the length of the credit card numbers.
B. Use a custom encryption algorithm to encrypt the data and store the data on an Amazon SageMaker instance in a VPC. Use the SageMaker DeepAR algorithm to randomize the credit card numbers.
C. Use AWS KMS to encrypt the data on Amazon S3 and Amazon SageMaker, and redact the credit card numbers from the customer data with AWS Glue.
D. Use an 1AM policy to encrypt the data on the Amazon S3 bucket and Amazon Kinesis to automatically discard credit card numbers and insert fake credit card numbers.
Answer: D

NEW QUESTION: 4

A. Option C
B. Option A
C. Option D
D. Option B
Answer: A,C


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