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NEW QUESTION: 1
What is a Hadoop Distributed File System (HDFS) typically used for?
A. Operational systems and transactional data
B. Data lakes
C. ERP systems
D. Data warehouses
Answer: B

NEW QUESTION: 2
The Cisco Unified Communications system of a company has five types of devices:
*Cisco Jabber Desktop
*CP-7965
*DX-650
*EX-60
*MX-200
Which two types of devices are affected when an engineer changes the DSCP for Video Calls service parameter?
(Choose two.)
A. MX-200
B. Cisco Jabber Desktop
C. DX-650
D. EX-60
E. CP-7965
Answer: C,E

NEW QUESTION: 3
A System Administrator wants to configure the Automated Service and Support Request feature.
Where can settings for this be configured.
A. Command Line Interface only
B. On SiteProtector only
C. On Local Management Interface, only during initial appliance setup
D. On Local Management Interface, only after initial appliance setup is complete
Answer: D
Explanation:
You can configure the IBM Security Network Protection appliance to automatically open a Service and Support Request in the IBM Customer Support system when serious errors occur. Use the Service and Support page to enable this feature.
You must use the local management interface to set up the automated Service and Support Request feature. This configuration is not currently supported in the SiteProtector System or the command line interface.
References:
https://www.ibm.com/support/knowledgecenter/en/SSHLHV_5.3.3/com.ibm.alps.doc/tasks/ alps_sending_support_request.htm

NEW QUESTION: 4
You create a batch inference pipeline by using the Azure ML SDK. You run the pipeline by using the following code:
from azureml.pipeline.core import Pipeline
from azureml.core.experiment import Experiment
pipeline = Pipeline(workspace=ws, steps=[parallelrun_step])
pipeline_run = Experiment(ws, 'batch_pipeline').submit(pipeline)
You need to monitor the progress of the pipeline execution.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. Option C
B. Option D
C. Option A
D. Option B
E. Option E
Answer: B,E
Explanation:
A batch inference job can take a long time to finish. This example monitors progress by using a Jupyter widget. You can also manage the job's progress by using:
* Azure Machine Learning Studio.
* Console output from the PipelineRun object.
from azureml.widgets import RunDetails
RunDetails(pipeline_run).show()
pipeline_run.wait_for_completion(show_output=True)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-parallel-run-step#monitor-the-parallel-run-job