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NEW QUESTION: 1
You are a database developer and you have about two years experience in creating business intelligence (BI) solutions by using SQL Server2008.
Now you are employed in a company which is named NaproStar and work as the technical support for the company which uses SQL Server2008 Analysis Services (SSAS).
To meet the business development, (SSAS) is used to create a data mining model and the Data Mining Extensions (DMX) code is used to create a mining structure.
The Data Mining Extensions (DMX) code is shown as the following:
Now you are assigned the following tasks:
Make sure that the Microsoft Decision Trees algorithm is used by the model. Have a mining model that can be processed by this mining structure created.
So of the following DMX statements, which one should be used to accomplish the tasks above?
A. ALTER MINING STRUCTURE [Bike Buyer]ADD MINING MODEL [Decision Tree] ( [Customer Key], [Age], [Bike Buyer] PREDICT, [Commute Distance], [Yearly Income]) USING 116 Microsoft_Decision_TreesWITH DRILLTHROUGH
B. CREATE MINING MODEL [Decision Tree] ( [Customer Key] LONG KEY, [Age] LONG DISCRETIZED (Automatic, 10), [Bike Buyer] LONG DISCRETE, [Commute Distance] TEXT DISCRETE, [Yearly Income] DOUBLE CONTINUOUS) USING Microsoft_Decision_Trees
C. SELECT * INTO [Decision Tree]USING [Microsoft_Decision_Trees]FROM [Bike Buyer]
D. INSERT INTO [Decision Tree] ( [Customer Key], [Age], [Bike Buyer], [Commute Distance], [Yearly Income]) OPENQUERY([Bike Buyer], 'Select [Customer Key], [Age], [Bike Buyer] , [Commute Distance],[Yearly Income]')
Answer: A

NEW QUESTION: 2
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
* Serve as a repository (or high volumes of large files in various formats.
* Implement optimized storage for big data analytics workloads.
* Ensure that data can be organized using a hierarchical structure.
Batch processing:
* Use a managed solution for in-memory computation processing.
* Natively support Scala, Python, and R programming languages.
* Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
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
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is

NEW QUESTION: 3
Which redundancy mode is adopted by the power supplies in the OceanStor 5300 V3 with 2 U enclosure?
A. 2+2
B. 4+4
C. 2+1
D. 1+1
Answer: D