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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 to 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 configure data loading for the tables.
Which data loading technology should you use for each table? To answer, select the appropriate options in the answer area.

Answer:
Explanation:

Explanation

Scenario: The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
Box 1: Change Tracking
Box 2: Change Tracking
Box 3: Temporal Table
Temporal Tables are generally useful in scenarios that require tracking history of data changes.
We recommend you to consider Temporal Tables in the following use cases for major productivity benefits.
* Slowly-Changing Dimensions
Dimensions in data warehousing typically contain relatively static data about entities such as geographical locations, customers, or products.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/tables/temporal-table-usage-scenarios

NEW QUESTION: 2
A start-up company has a web application based in the us-east-1 Region with multiple Amazon EC2 instances running behind an Application Load Balancer across multiple Availability Zones. As the company's user base grows in the us-west-1 Region, it needs a solution with low latency and high availability.
What should a solutions architect do to accomplish this?
A. Provision EC2 instances and an Application Load Balancer in us-west-1. Make the load balancer distribute the traffic based on the location of the request.
B. Provision EC2 instances and configure an Application Load Balancer in us-west-1. Create an accelerator in AWS Global Accelerator that uses an endpoint group that includes the load balancer endpoints in both Regions.
C. Provision EC2 instances and configure an Application Load Balancer in us-west-1. Configure Amazon Route 53 with a weighted routing policy. Create alias records in Route 53 that point to the Application Load Balancer.
D. Provision EC2 instances in us-west-1. Switch the Application Load Balancer to a Network Load Balancer to achieve cross-Region load balancing.
Answer: B
Explanation:
Explanation
https://aws.amazon.com/global-accelerator/faqs/
Register endpoints for endpoint groups: You register one or more regional resources, such as Application Load Balancers, Network Load Balancers, EC2 Instances, or Elastic IP addresses, in each endpoint group. Then you can set weights to choose how much traffic is routed to each endpoint.
Endpoints in AWS Global Accelerator
Endpoints in AWS Global Accelerator can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses. A static IP address serves as a single point of contact for clients, and Global Accelerator then distributes incoming traffic across healthy endpoints. Global Accelerator directs traffic to endpoints by using the port (or port range) that you specify for the listener that the endpoint group for the endpoint belongs to.
Each endpoint group can have multiple endpoints. You can add each endpoint to multiple endpoint groups, but the endpoint groups must be associated with different listeners.
Global Accelerator continually monitors the health of all endpoints that are included in an endpoint group. It routes traffic only to the active endpoints that are healthy. If Global Accelerator doesn't have any healthy endpoints to route traffic to, it routes traffic to all endpoints.
https://docs.aws.amazon.com/global-accelerator/latest/dg/about-endpoints.html

NEW QUESTION: 3
HOTSPOT



Answer:
Explanation: