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NEW QUESTION: 1
Universal Containers recently rolled out a Community to its partners.
The internal sales team has the following requirements:
* Ability to support the addition of 50 new partners every month.
* Ability to pass leads to the partners.
* Continue to have access to the leads after transfer to a partner.
* Access to the Opportunity when the partner converts the lead.
* Leads should be visible to only the partner who is working on the lead.
Which sharing option should the Salesforce Administrator choose to meet the requirement for internal users?
A. Set OWD (Organization-Wide Default) to Private, create a sharing rule for Leads and Opportunities, and implement the Lead Inbox component.
B. Allow partner users to manually share the Leads and Opportunities with internal users.
C. Use Sharing Sets to share Leads and Opportunities so internal users can automatically access those records.
D. Create Lead and Opportunity Sharing Rules that share those records to a public group of partner users.
Answer: A

NEW QUESTION: 2
Welche Technik sollte ein Projektmanager in einer Situation anwenden, in der ein kollaborativer Ansatz für das Konfliktmanagement nicht möglich ist?
A. Konsens
B. Coaching
C. Vermeidung
D. Beeinflussen
Answer: C

NEW QUESTION: 3
What do Analytics apps do?
A. Use ready-made dashboards to tell easy-to-follow stories about your data
B. Let you add new types of charts to Salesforce
C. Let you create configuration wizards to make Analytics setup easier
D. Alert you when you need a visa for an upcoming trip
Answer: A

NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:

Does the solution meet the goal?
A. No
B. Yes
Answer: B
Explanation:
The two steps are present: process_step and train_step
Note:
Data used in pipeline can be produced by one step and consumed in another step by providing a PipelineData object as an output of one step and an input of one or more subsequent steps.
PipelineData objects are also used when constructing Pipelines to describe step dependencies. To specify that a step requires the output of another step as input, use a PipelineData object in the constructor of both steps.
For example, the pipeline train step depends on the process_step_output output of the pipeline process step:
from azureml.pipeline.core import Pipeline, PipelineData
from azureml.pipeline.steps import PythonScriptStep
datastore = ws.get_default_datastore()
process_step_output = PipelineData("processed_data", datastore=datastore) process_step = PythonScriptStep(script_name="process.py", arguments=["--data_for_train", process_step_output], outputs=[process_step_output], compute_target=aml_compute, source_directory=process_directory) train_step = PythonScriptStep(script_name="train.py", arguments=["--data_for_train", process_step_output], inputs=[process_step_output], compute_target=aml_compute, source_directory=train_directory) pipeline = Pipeline(workspace=ws, steps=[process_step, train_step]) Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azure-ml-py