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NEW QUESTION: 1
You need to recommend an appropriate solution for the data mining requirements.
Which solution should you recommend?
A. Use Azure HPC Scheduler Tools to schedule jobs and automate scaling of virtual machines.
B. Use Traffic Manager to allocate tasks to multiple virtual machines, and use the Azure Portal to spin up new virtual machines as needed.
C. Use Windows Server HPC Pack on-premises to schedule jobs and automate scaling of virtual machines in Azure.
D. Design a schedule process that allocates tasks to multiple virtual machines, and use the Azure Portal to create new VMs as needed.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
B: Azure HPC provides Virtual Machines with RDMA and 8 or more processor cores.
Incorrect Answers:
A, C: Involves manually scaling. Requirements are for automatic scaling - "Allow the number of processor cores dedicated to an analysis to grow and shrink automatically based on the demand of the analysis." D: Is an on-premises solution. - "The company plans to replace the existing on- premises cluster with a cloud-based solution." Requirements: https://azure.microsoft.com/en-us/documentation/articles/virtual-machines-a8-a9-a10-a11- specs/ Testlet 1 Background Overview Northwind Electric Cars is the premier provider of private, low-cost transportation in Denver. Northwind drivers are company employees who work together as a team. The founding partners believe that by hiring their drivers as employees, their drivers focus on providing a great customer experience. Northwind Electric Cars has a reputation for offering fast, reliable, and friendly service, due largely to their extensive network of drivers and their proprietary dispatching software named NorthRide.
Northwind Electric Cars drivers depend on frequent, automatic updates for the NorthRide mobile app. The Northwind management team is concerned about unplanned system downtime and slow connection speeds caused by high usage. Additionally, Northwind's in- house data storage solution is unsustainable because of the new influx of customer data that is retained. Data backups are made periodically on DVDs and stored on-premises at corporate headquarters.
Apps
NorthRide App
Northwind drivers use the NorthRide app to meet customer pickup requests. The app uses a GPS transponder in each Northwind vehicle and Bing Maps APIs to monitor the location of each vehicle in the fleet in real time. NorthRide allows Northwind dispatchers to optimize their driver coverage throughout the city.
When new customers call, the dispatcher enters their pickup locations into NorthRide. NorthRide identifies the closest available driver. The dispatcher then contacts the driver with the pick-up details. This process usually results in a pick-up time that is far faster than the industry average. Drivers use NorthRide to track the number of miles they drive and the number of customers they transport. Drivers also track their progress towards their established goals, which are measured by using key performance indicators (KPIs).
NorthRide App 2.0
Northwind Electric Cars is growing quickly. New callers often wait for their calls to be answered because the dispatchers are contacting their drivers to arrange pickups for other customers.
To support the growth of the business, Northwind's development team completes an overhaul of the NorthRide system that it has named NorthRide 2.0. When a dispatcher enters a customer's pickup location, the address and driving directions are automatically sent to the driver who is closest to the customer's pickup location.
Drivers indicate their availability on the NorthRide mobile app and can view progress towards their KPI's in real time. Drivers can also record customer ratings and feedback for each pickup.
Business Requirements
Apps
NorthRideFinder App
Northwind Electric Cars needs a customer-facing website and mobile app that allows customers to schedule pickups. Customers should also be able to create profiles that will help ensure the customer gets a ride faster by storing customer information.
Predictor App
Northwind Electric Cars needs a new solution named Predictor. Predictor is an employee- facing mobile app. The app predicts periods of high usage and popular pickup locations and provides various ways to view this predictive data. Northwind uses this information to better distribute its drivers. Northwind wants to use the latest Azure technology to create this solution.
Other Requirements
On-premises data must be constantly backed up.

Mobile data must be protected from loss, even if connectivity with the backend is lost.

Dispatch offices need to have seamless access to both their primary data center and the applications

and services that are hosted in the Azure cloud. Connectivity needs to be redundant to on-premises and cloud services, while providing a way for each dispatch office to continue to operate even if one or all of the connection options fail. The management team requires that operational data is accessible
24/7 from any office location.
Technical Requirements
Apps and Website
NorthRide / NorthRideFinder Apps:
The solution must support on-premises and Azure data storage.

The solution must scale as necessary based on the current number of concurrent users.

Customer pickup requests from NorthRideFinder must be asynchronous.

The customer pickup request system will be high in volume, and each request will have a short life

span.
Data for NorthRideFinder must be protected during a loss of connectivity.

NorthRide users must authenticate to the company's Azure Active Directory.

Northwind Public Website
The customer website must use a WebJob to process profile images into thumbnails

The customer website must be developed with lowest cost and difficulty in mind.

The customer website must automatically scale to minimize response times for customers.

Other Requirements
Data Storage:
The data storage must interface with an on-premises Microsoft SQL backend database.

A disaster recovery system needs to be in place for large amounts of data that will backup to Azure.

Backups must be fully automated and managed the Azure Management Portal.

The recovery system for company data must use a hybrid solution to back up both the on-premises

Microsoft SQL backend and any Azure storage.
Predictive Routing:
An Azure solution must be used for prediction systems.

Predictive analytics must be published as a web service and accessible by using the REST API.

Security:
The NorthRide app must use an additional level of authentication other than the employee's password.

Access must be secured in NorthRide without opening a firewall port.

Company policy prohibits inbound connections from internet callers to the on- premises network.

Customer usernames in NorthRideFinder cannot exceed 10 characters.

Customer data in NorthRideFinder can be received only by the user ID that is associated with the data.

NEW QUESTION: 2


A. OSPF
B. EIGRP
C. BGP
D. RIP
Answer: B

NEW QUESTION: 3
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. Use a granularity of two days.
B. Create 730 partitions.
C. Create 17,520 partitions.
D. Create 2,557 partitions.
Answer: D
Explanation:
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.