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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You are designing the real-time portion of the input stream processing. The input will be a continuous stream of data and each record will be processed one at a time. The data will come from an Apache Kafka producer.
You need to identify which HDInsight cluster to use for the final processing of the input data. This will be used to generate continuous statistics and real-time analytics. The latency to process each record must be less than one millisecond and tasks must be performed in parallel.
Which type of cluster should you identify?
A. Apache Spark
B. Apache Storm
C. Apache HBase
D. Apache Hadoop
NEW QUESTION: 2
Universal Containers has the following Discount Schedule attached to product L.
Product L is a Product Option for two bundles, A and B.
A user at Universal Containers has added both bundles to a Quote. In Bundle A, Product L has a Quantity of 7.
In Bundle B, Product L has a Quantity of 8. On this Quote, however, both Product Options are being discounted using the second tier in the table above. Which two actions allow both Product Options to be discounted using the first tier?
A. Set the Aggregation Scope field on the Discount Schedule to None, as well as uncheck Cross Products.
B. Change the Product Option Type for Product L to Related Product in both Bundles.
C. Move Discount Schedule X from Product L to the corresponding Product Option records in each Bundle.
D. Apply a separate discount schedule to the Product Option records in each Bundle.
NEW QUESTION: 3
A. List Page
B. Advanced Find Query
C. Custom Reports
D. Enterprise Search
E. Role Center
NEW QUESTION: 4
You have an Azure subscription that contains the following resources:
* An Azure Active Directory (Azure AD) tenant that contains a security group named Group1.
* An Azure Synapse Analytics SQL pool named Pool1.
You need to control the access of Group1 to specific columns and rows in a table in Pool1 Which Transact-SQL commands should you use? To answer, select the appropriate options in the answer area.
NOTE: Each appropriate options in the answer area.