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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 a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
Implement table partitioning to improve the manageability of the data warehouse and to avoid the need
to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
Partition the Fact.Order table and retain a total of seven years of data.
Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition
structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date
tables.
Incrementally load all tables in the database and ensure that all incremental changes are processed.
Maximize the performance during the data loading process for the Fact.Order partition.
Ensure that historical data remains online and available for querying.
Reduce ongoing storage costs while maintaining query performance for current data.
You are not permitted to make changes to the client applications.
You need to implement the data partitioning strategy.
How should you partition the Fact.Order table?
A. Create 17,520 partitions.
B. Create 2,557 partitions.
C. Create 730 partitions.
D. Use a granularity of two days.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
We create on partition for each day. 7 years times 365 days is 2,555. Make that 2,557 to provide for leap years.
From scenario: Partition the Fact.Order table and retain a total of seven years of data.
Maximize the performance during the data loading process for the Fact.Order partition.
NEW QUESTION: 2
Which VM type resides in the VM home namespace object on a vSAN datastore?
A. .vswp
B. .vmx
C. .vmem
D. .vmsn
Answer: B
NEW QUESTION: 3
会社は複数のWebサイトからクリックストリームデータをキャプチャし、バッチ処理を使用してそれを分析します。データは毎晩Amazon Redshiftに読み込まれ、ビジネスアナリストによって消費されます。同社は、タイムリーな洞察を得るために、ほぼリアルタイムのデータ処理に移行したいと考えています。このソリューションでは、最小限の労力と運用オーバーヘッドでストリーミングデータを処理する必要があります。
このソリューションで最も費用効果の高いAWSサービスの組み合わせはどれですか？ （2つ選択してください。）
A. Amazon EC2
B. Amazon Kinesis Data Analytics
C. AWSLambda
D. Amazon Kinesis Data Firehose
E. Amazon Kinesis Data Streams
Answer: B,E
Explanation:
Explanation
Kinesis Data Streams and Kinesis Client Library (KCL) - Data from the data source can be continuously captured and streamed in near real-time using Kinesis Data Streams.
With the Kinesis Client Library (KCL), you can build your own application that can preprocess the streaming data as they arrive and emit the data for generating incremental views and downstream analysis.
Kinesis Data Analytics - This service provides the easiest way to process the data that is streaming through Kinesis Data Stream or Kinesis Data Firehose using SQL. This enables customers to gain actionable insight in near real-time from the incremental stream before storing it in Amazon S3.
https://d1.awsstatic.com/whitepapers/lambda-architecure-on-for-batch-aws.pdf
NEW QUESTION: 4
You need to create a virtual machine template for the web servers used by the CRM application. The solution must meet the virtualization requirements.
Virtualization Requirements
The company identifies the following virtualization requirements:
Minimize the number of permissions and privileges assigned to users.
Ensure that the members of a group named Group2 can add a WSUS server to the fabric.
Ensure that a diagram view of the virtualization environment can be generated dynamically.
Minimize the amount of administrative effort required to manage the virtualization environment.
Prevent the failure of a front-end web server from affecting the availability of the CRM application.
Ensure that the members of a group named Group1 can create new virtual machines in the Los Angeles office only.
Only create virtual machine templates by using objects that already exist in the System Center 2012 Virtual Machine Manager (VMM) library.
On the failover cluster in the main office, apply limited distribution release (LDR) updates to the
virtualization hosts without disrupting the virtual machines hosted on the virtualization hosts.
What should you use?
A. A virtual hard disk (VHD)
B. An .iso image
C. A Windows PowerShell script
D. A virtual machine
Answer: A