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NEW QUESTION: 1
In a claims process, a human task is modeled for the activity in which a call center representative needs to contact a customer to request additional details on an active claim. If the customer is not contacted within 24 hours of the claim, an escalation procedure is activated and a notification is sent to the call center supervisor every hour. Identify the attributes to model the human task escalation requirements.
A. The Primary owner, the Escalation name, Description and Notification attributes.
B. The Primary owner, the Escalation name, the Escalation condition, and Escalation action.
C. The Escalation name, the Escalation condition, and Escalation action.
D. The Escalation name, Description and Notification attributes.
Answer: C
NEW QUESTION: 2
You are designing an order processing system in Azure that will contain the Azure resources shown in the following table.
The order processing system will have the following transaction flow:
A customer will place an order by using App1.
When the order is received, App1 will generate a message to check for product availability at vendor 1 and vendor 2.
An integration component will process the message, and then trigger either Function1 or Function2 depending on the type of order.
Once a vendor confirms the product availability, a status message for App1 will be generated by Function1 or Function2.
All the steps of the transaction will be logged to storage1.
Which type of resource should you recommend for the integration component?
Which type of resource should you recommend for the integration component?
A. an Azure Service Bus queue
B. an Azure Event Grid domain
C. an Azure Event Hubs capture
D. an Azure Data Factory pipeline
Answer: D
Explanation:
A data factory can have one or more pipelines. A pipeline is a logical grouping of activities that together perform a task.
The activities in a pipeline define actions to perform on your data.
Data Factory has three groupings of activities: data movement activities, data transformation activities, and control activities.
Azure Functions is now integrated with Azure Data Factory, allowing you to run an Azure function as a step in your data factory pipelines.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipelines-activities
NEW QUESTION: 3
Ein Projektmanager führt mit seinem kürzlich erworbenen Team eine agile Release-Planung durch. Sie sind bestrebt, zusammenzuarbeiten, um hervorragende Ergebnisse zu erzielen. Der Kunde bittet wegen mangelnder technischer Kenntnisse um ein Produkt mit begrenzten Anforderungen.
Was sollte der Projektmanager tun, um sicherzustellen, dass der Kunde mit dem Endprodukt zufrieden ist?
A. Fügen Sie dem Endprodukt weitere Funktionen hinzu
B. Lassen Sie den Kunden einen eigenen technischen Ingenieur zur Verfügung stellen
C. Legen Sie die Anforderungen in einem unterzeichneten Vertrag fest
D. Binden Sie den Client in jede Iteration ein
Answer: D
NEW QUESTION: 4
Which three statements are true about adaptive SQL plan management?
A. It adds new, bettor plans automatically as fixed plans to the baseline.
B. It automatically performs verification or evolves non-accepted plans, in
COMPREHENSIVE mode when they perform better than existing accepted plans.
C. The non-accepted plans are automatically accepted and become usable by the optimizer if they perform better than the existing accepted plans.
D. The optimizer always uses the fixed plan, if the fixed plan exists in the planbaseline.
E. The non-accepted plansin a SQL plan baseline are automatically evolved, in
COMPREHENSIVE mode, during the nightly maintenance window and a persistent verification report is generated.
Answer: B,C,E
Explanation:
With adaptive SQL plan management, DBAs no longer have to manually run the verification or evolve process for non-accepted plans. When automatic SQL tuning is in
COMPREHENSIVE mode, it runs a verification or evolve process for all SQL statements that have non-accepted plans during the nightly maintenance window. If thenon-accepted plan performs better than the existing accepted plan (or plans) in the SQL plan baseline, then the plan is automatically accepted and becomes usable by the optimizer. After the verification is complete, a persistent report is generated detailing how the non-accepted plan performs compared to the accepted plan performance. Because the evolve process is now an AUTOTASK, DBAs can also schedule their own evolve job at end time.
Note:
* The optimizer is able to adapt plans on the fly by predetermining multiple subplans for portions of the plan.
* Adaptive plans, introduced in Oracle Database 12c, enable the optimizer to defer the final plan decision for a statement until execution time. The optimizer instruments its chosen plan (the default plan) with statistics collectors so that it can detect at runtime, if its cardinality estimates differ greatly from the actual number of rows seen by the operations in the plan. If there is a significant difference, then the plan or a portion of it will be automatically adapted to avoid suboptimal performance on the first execution of a SQL statement.
References:
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