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NEW QUESTION: 1
Which two are prerequisites for performing a flashback transaction?
A. Flashback Database must be enabled.
B. Recycle bin must be enabled for the database.
C. Supplemental logging must be enabled.
D. EXECUTE privilege on the DBMS_FLASHBACK package must be granted to the user flashing back transaction.
E. Undo retention guarantee for the database must be configured.
F. Block change tracking must be enabled tor the database.
Answer: C,D
Explanation:
http://docs.oracle.com/cd/E11882_01/appdev.112/e41502/adfns_flashback.htm#ADFNS611
To configure your database for the Flashback Transaction feature, you or your database
administrator must:
With the database mounted but not open, enable ARCHIVELOG:
ALTER DATABASE ARCHIVELOG;
Open at least one archive log:
ALTER SYSTEM ARCHIVE LOG CURRENT;
If not done, enable minimal and primary key supplemental logging:
ALTER DATABASE ADD SUPPLEMENTAL LOG DATA;
ALTER DATABASE ADD SUPPLEMENTAL LOG DATA (PRIMARY KEY) COLUMNS;
If you want to track foreign key dependencies, enable foreign key supplemental logging:
ALTER DATABASE ADD SUPPLEMENTAL LOG DATA (FOREIGN KEY) COLUMNS;
Reference: Oracle Database Advanced Application Developer's Guide 11g, Using Oracle
Flashback Technology

NEW QUESTION: 2
DRAG DROP
You manage a bot in a serverless architecture.
The bot provides custom responses to questions based upon the identity of the user.
The bot must meet the following requirements:
Identify the user by face.
Provide text-to-speech reading of questions to the user.
Analyze the text of the user's responses for patterns.
What should you recommend? To answer, drag the appropriate solution to the correct scenario. Each solution may be used once, more than once, or not at all. You may need to drag the split bar between panes to scroll or view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Note: With Azure, built-in intelligence is within the reach of all app developers. Enable your serverless code or logic to use Machine Learning and Cognitive Services.
Box 1, Identify users by face: Azure Cognitive Services
Microsoft Face API, a cloud-based service that provides the most advanced face algorithms. Face API has two main functions: face detection with attributes and face recognition.
Box 2, Provide text-to-speech services: Azure Cognitive Services
Infuse your apps, websites and bots with intelligent algorithms to see, hear, speak, understand and interpret your user needs through natural methods of communication.
Example:
Speech: Convert spoken audio into text, use voice for verification, or add speaker recognition to your app.
Box 3, Read questions to users: Azure Functions
Azure Functions is a serverless solution.

NEW QUESTION: 3
A company has developed several AWS Glue jobs to validate and transform its data from Amazon S3 and load it into Amazon RDS for MySQL in batches once every day. The ETL jobs read the S3 data using a DynamicFrame. Currently, the ETL developers are experiencing challenges in processing only the incremental data on every run, as the AWS Glue job processes all the S3 input data on each run.
Which approach would allow the developers to solve the issue with minimal coding effort?
A. Have the ETL jobs delete the processed objects or data from Amazon S3 after each run.
B. Have the ETL jobs read the data from Amazon S3 using a DataFrame.
C. Enable job bookmarks on the AWS Glue jobs.
D. Create custom logic on the ETL jobs to track the processed S3 objects.
Answer: A