Note: This question is part of a series of questions that present the same Scenario.Each question I the series contains

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Note: This question is part of a series of questions that present the same Scenario.Each question I 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 correct solution.Start of Repeated Scenario:initial data that contains the crime data from major cities.You plan to build training models from the training data. You plan to automate the process of adding more data to the training models and to training 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) increased crime risk at a particular time and ptace. incoming data stream fromFacebook. which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds. 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 AzureHDInsight cluster types tor the various tasks associated to the processing pipeline.End of repeated Scenario.You are planning a storage strategy for a large amount of analytic data used for the crime100 billion records, and more thantwo billion records will be added daily.You already created an Apache Hadoop cluster in HDInsight premium.You need to implement the storage strategy to meet the following requirements: The storage capacity must support 50 TB. The storage must he optimized tor Hadoop. The data must be stored in its native format Enterprise-level security based on Active Directory must be supported.What should you create?Window, that has premium storage- a G-series size,and uses Microsoft SQL Server 2016 to store the dataB. an Azure Data Lake Analytics service by using Azure Power ShellC. an Azure Data Lake S