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NEW QUESTION: 1
How should you complete the GROUP BY clause to meet the Streaming Analytics requirements?
A. GROUP BY SlidingWindow(Second, 30)
B. GROUP BY SessionWindow(Second, 30, 60)
C. GROUP BY HoppingWindow(Second, 60, 30)
D. GROUP BY TumblingWindow(Second, 30)
Answer: D
Explanation:
Scenario: You plan to use a 30-second period to calculate the average temperature reading of the sensors.
Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.
InAnswers:
A: Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap, so events can belong to more than one Hopping window result set.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions
Topic 1, Contoso
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Existing Environment. Current State of Development
Contoso produces a set of Bluetooth sensors that read the temperature and humidity. The sensors connect to IoT gateway devices that relay the data.
All the IoT gateway devices connect to an Azure IoT hub named iothub1.
Existing Environment. Device Twin
You plan to implement device twins by using the following JSON sample.

Existing Environment. Azure Stream Analytics
Each room will have between three to five sensors that will generate readings that are sent to a single IoT gateway device. The IoT gateway device will forward all the readings to iothub1 at intervals of between 10 and 60 seconds.
You plan to use a gateway pattern so that each IoT gateway device will have its own IoT Hub device identity.
You draft the following query, which is missing the GROUP BY clause.
SELECT
AVG(temperature),
System.TimeStamp() AS AsaTime
FROM
Iothub
You plan to use a 30-second period to calculate the average temperature reading of the sensors.
You plan to minimize latency between the condition reported by the sensors and the corresponding alert issued by the Stream Analytics job.
Existing Environment. Device Messages
The IoT gateway devices will send messages that contain the following JSON data whenever the temperature exceeds a specified threshold.

The level property will be used to route the messages to an Azure Service Bus queue endpoint named criticalep.
Existing Environment. Issues
You discover connectivity issues between the IoT gateway devices and iothub1, which cause IoT devices to lose connectivity and messages.
Requirements. Planning Changes
Contoso plans to make the following changes:
Use Stream Analytics to process and view data.
Use Azure Time Series Insights to visualize data.
Implement a system to sync device statuses and required settings.
Add extra information to messages by using message enrichment.
Create a notification system to send an alert if a condition exceeds a specified threshold.
Implement a system to identify what causes the intermittent connection issues and lost messages.
Requirements. Technical Requirements
Contoso must meet the following requirements:
Use the built-in functions of IoT Hub whenever possible.
Minimize hardware and software costs whenever possible.
Minimize administrative effort to provision devices at scale.
Implement a system to trace message flow to and from iothub1.
Minimize the amount of custom coding required to implement the planned changes.
Prevent read operations from being negatively affected when you implement additional services.

NEW QUESTION: 2

A. Option C
B. Option A
C. Option D
D. Option B
Answer: C
Explanation:
Ref: http://technet.microsoft.com/en-us/library/dn282281.aspx

NEW QUESTION: 3
Which IPS technique commonly is used to improve accuracy and context awareness, aiming to detect and respond to relevant incidents only and therefore, reduce noise?
A. Attack relevancy
B. Target asset value
C. Signature accuracy
D. Risk rating
Answer: D
Explanation:
http://www.cisco.com/en/US/prod/collateral/vpndevc/ps5729/ps5713/ps4077/prod_white_paper09 00aecd806e7299.html
Risk Rating Calculation Risk rating is a quantitative measure of your network's threat level before IPS mitigation. For each event fired by IPS signatures, Cisco IPS Sensor Software calculates a risk rating number. The factors used to calculate risk rating are:
Signature fidelity rating: This IPS-generated variable indicates the degree of attack certainty.
Attack severity rating: This IPS-generated variable indicates the amount of damage an attack
can cause.
Target value rating: This user-defined variable indicates the criticality of the attack target. This is the only factor in risk rating that is routinely maintained by the user. You can assign a target value rating per IP address in Cisco IPS Device Manager or Cisco Security Manager. The target value rating can raise or lower the overall risk rating for a network device. You can assign the following target values:
-
75: Low asset value
-
100: Medium asset value
-
200: Mission-critical asset value
Attack relevancy rating: This IPS-generated value indicates the vulnerability of the attack target.
Promiscuous deltA. The risk rating of an IPS deployed in promiscuous mode is reduced by the promiscuous delta. This is because promiscuous sensing is less accurate than inline sensing. The promiscuous delta can be configured on a per-signature basis, with a value range of 0 to 30. (The promiscuous delta was introduced in Cisco IPS Sensor Software Version 6.0.)
Watch list rating: This IPS-generated value is based on data found in the Cisco Security Agent watch list. The Cisco Security Agent watch list contains IP addresses of devices involved in network scans or possibly contaminated by viruses or worms. If an attacker is found on the watch list, the watch list rating for that attacker is added to the risk rating. The value for this factor is between 0 and 35. (The watch list rating was introduced in Cisco IPS Sensor Software Version 6.0.) Risk rating can help enhance your productivity as it intelligently assesses the level of risk of each event and helps you focus on high-risk events.