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NEW QUESTION: 1
What must occur before a bank's Chief Marketing Officer can understand the sentiments social media
users are expressing about the bank's credit cards?
A. Monitor social media events in real time. Analyzing unstructured streaming data is necessary to
produce immediately actionable insights.
B. Add sentiment metrics into the data warehouse. This trusted structured information source is
guaranteed to yield reproducible, high quality reports.
C. Buy a service offering from Twitter which provides insights into the behaviors of the bank's customers.
The bank will need to disclose the customer names.
D. Get access to a social media analytics platform. Unstructured data extracted from many external
sources are analyzed in relevant context.
Answer: B

NEW QUESTION: 2
Click the Exhibit button.
In the exhibit, which two statements are true? (Choose two.)

A. The configuration defines two MLPPP bundles.
B. The configuration specifies that the bundle(s) will be up if there are at least three configured member links and at least three are active.
C. The configuration defines a single MLPPP bundle.
D. The configuration specifies that the bundle(s) will be up if there are at least three configured member links and at least one is active .
Answer: B,C

NEW QUESTION: 3

A. Option C
B. Option B
C. Option D
D. Option A
Answer: B,C
Explanation:
https://docs.citrix.com/ja-jp/netscaler/11/netscaler-hardware-installation/netscaler-initial-configuration.html

NEW QUESTION: 4
You need to develop a pipeline for processing data. The pipeline must meet the following requirements.
* Scale up and down resources for cost reduction.
* Use an in-memory data processing engine to speed up ETL and machine learning operations.
* Use streaming capabilities.
* Provide the ability to code in SQL, Python, Scala, and R.
* Integrate workspace collaboration with Git.
What should you use?
A. Azure Stream Analytics
B. HDInsight Hadoop Cluster
C. HDInsight Spark Cluster
D. Azure SQL Data Warehouse
Answer: C
Explanation:
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
You can create an HDInsight Spark cluster using an Azure Resource Manager template. The template can be found in GitHub.
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing