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NEW QUESTION: 1
Which AWS managed service is used to host databases?
A. AWS Data Pipeline
B. AWS Batch
C. Amazon RDS
D. AWS Artifact
Answer: C
Explanation:
Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need.

NEW QUESTION: 2
What two options are causes of network slowness that can result from inter-VLAN routing problems? (Choose two.)
A. Hardware forwarding issues
B. DTP disabled on a switchport
C. BPDU guard enabled on a switchport
D. Root guard disabled on an EtherChannel
E. Packet loss
Answer: A,E
Explanation:
Causes for Network Slowness
Packet Loss
In most cases, a network is considered slow when higher-layer protocols (applications) require extended time to complete an operation that typically runs faster. That slowness is caused by the loss of some packets on the network, which causes higher-level protocols like TCP or applications to time out and initiate retransmission.
Hardware Forwarding Issues
With another type of slowness, caused by network equipment, forwarding (whether Layer 2 [L2] or L3) is performed slowly. This is due to a deviation from normal (designed) operation and switching to slow path forwarding. An example of this is when Multilayer Switching (MLS) on the switch forwards L3 packets between VLANs in the hardware, but due to misconfiguration, MLS is not functioning properly and forwarding is done by the router in the software (which drops the interVLAN forwarding rate significantly).
Reference: https://www.cisco.com/c/en/us/support/docs/lan-switching/virtual-lans-vlan-trunking- protocol-vlans-vtp/23637-slow-int-vlan-connect.html#common_causes

NEW QUESTION: 3
You are designing a data warehouse for a fresh food distribution business that stores sales by individual product. It stores sales targets by product category. Products are classified into subcategories and categories.
Each product is included in only a single product subcategory, and each subcategory is included in only a single category.
The data warehouse will be a data source for an Analysis Services cube.
The data warehouse contains two fact tables:
factSales, used to record daily sales by product
factProductTarget, used to record the monthly sales targets by product category
Reports must be developed against the warehouse that reports product sales by product, category and subcategory, and product sales targets.
You need to design the product dimension. The solution should use as few tables as possible while supporting all the requirements.
What should you do?
A. Create one product table, dimProduct, which contains product detail, category, and subcategory columns. Connect factSales to dimProduct with a foreign key constraint. Direct the cube developer to use a non-key granularity attribute for factProductTarget.
B. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory. Connect factSales to all three product tables and connect factProductTarget to dimProductCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.
C. Create two product tables, dimProduct and dimProductCategory. Connect factSales to dimProduct and factProductTarget to dimProductCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.
D. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory, and a fourth bridge table that joins products to their appropriate category and subcategory table records with foreign key constraints. Direct the cube developer to use key granularity attributes.
Answer: A