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NEW QUESTION: 1
Your company Is moving towards tracking web page users with a small tracking Image loaded on each
page Currently you are serving this image out of US-East, but are starting to get concerned about the time
It takes to load the image for users on the west coast.
What are the two best ways to speed up serving this image? Choose 2 answers
A. Serve the image out of S3 so that it isn't being served of your web application tier
B. Serve the image out through CloudFront
C. Use Route 53's Latency Based Routing and serve the image out of US-West-2 as well as US-East-1
D. Use EBS PIOPs to serve the image faster out of your EC2 instances
Answer: B,C

NEW QUESTION: 2
Ein Projektmanager, der an einem komplexen System arbeitet, weiß, dass das Unternehmen 50 Prozent seiner Softwarekosten für die Wartung von Systemen ausgibt. Der Projektmanager schlägt dem Management vor, die Wartungskosten zu senken, wenn die Organisation mithilfe der CMMl (Capability Maturity Model Integration) bewertet wird.
Welchen Wissensbereich des Projektmanagements wird sich diese Bewertung auswirken *?
A. Projektkostenmanagement
B. Projektintegrationsmanagement
C. Projektqualitätsmanagement
D. Projektumfangsverwaltung
Answer: A

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