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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 optimize data loading for the Dimension.Customer table.
Which three Transact-SQL segments should you use to develop the solution? To answer, move the appropriate Transact-SQL segments from the list of Transact-SQL segments to the answer area and arrange them in the correct order.
NOTE: You will not need all of the Transact-SQL segments.

Answer:
Explanation:

Explanation

Step 1: USE DB1
From Scenario: 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.
Step 2: EXEC sys.sp_cdc_enable_db
Before you can enable a table for change data capture, the database must be enabled. To enable the database, use the sys.sp_cdc_enable_db stored procedure.
sys.sp_cdc_enable_db has no parameters.
Step 3: EXEC sys.sp_cdc_enable_table
@source schema = N 'schema' etc.
Sys.sp_cdc_enable_table enables change data capture for the specified source table in the current database.
Partial syntax:
sys.sp_cdc_enable_table
[ @source_schema = ] 'source_schema',
[ @source_name = ] 'source_name' , [,[ @capture_instance = ] 'capture_instance' ]
[,[ @supports_net_changes = ] supports_net_changes ]
Etc.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sys-sp-cdc-enable-table-trans
https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sys-sp-cdc-enable-db-transac

NEW QUESTION: 2
Case Study: 4 - Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
* Redis - metadata, social graph, caching
* Application servers:
Tomcat - Java micro-services
* Nginx - static content
* Apache Beam - Batch processing
* Storage appliances:
iSCSI for VM hosts
* Fiber channel SAN - MySQL databases
* NAS - image storage, logs, backups
* Apache Hadoop/Spark servers:
Data analysis
* Real-time trending calculations
* MQ servers:
Messaging
* Social notifications
* Events
* Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
* Business Requirements
* Build a reliable and reproducible environment with scaled parity of production. Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud. Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud. Support failover of the production environment to cloud during an emergency. Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
For this question, refer to the Dress4Win case study.
You want to ensure Dress4Win's sales and tax records remain available for infrequent viewing by auditors for at least 10 years. Cost optimization is your top priority. Which cloud services should you choose?
A. BigQuery to store the data, and a web server cluster in a managed instance group to access the data. Google Cloud SQL mirrored across two distinct regions to store the data, and a Redis cluster in a managed instance group to access the data.
B. Google Cloud Storage Nearline to store the data, and gsutil to access the data.
C. Google Bigtabte with US or EU as location to store the data, and gcloud to access the data.
D. Google Cloud Storage Coldline to store the data, and gsutil to access the data.
Answer: D
Explanation:
References: https://cloud.google.com/storage/docs/storage-classes

NEW QUESTION: 3
What is the function of the detail-suppressed keyword in the aggregate command?
A. It only advertises the summarized routes to other BGP peers.
B. It advertises both the summarized routes and specific routes to other BGP peers.
C. It suppresses the delivery of specific routes to the IP routing table.
D. It suppresses the delivery of generated summarized routes to the IP routing table.
Answer: A