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NEW QUESTION: 1
When there is a significant change in accounting principle, an auditor's report should refer to the lack of
consistency in:
A. The opinion paragraph.
B. An explanatory paragraph between the second paragraph and the opinion paragraph.
C. The scope paragraph.
D. An explanatory paragraph following the opinion paragraph.
Answer: D
Explanation:
Explanation/Reference:
Explanation:
Choice "D" is correct. When there is a significant change in accounting principle, the auditor's report
should refer to the lack of consistency in an explanatory paragraph following the opinion paragraph. The
explanatory paragraph should identify the change and refer to the note in the FS that discusses the
change in detail. The auditor's concurrence with the change in GAAP is implicit, unless he or she takes
exception.
Choice "A" is incorrect. Lack of consistency is not a scope limitation.
Choice "B" is incorrect. An explanatory paragraph is often inserted between the second paragraph and
opinion paragraph. However, where a change is accounted for in accordance with GAAP, the explanatory
paragraph should follow the unqualified opinion paragraph.
Choice "C" is incorrect. The lack of consistency would not be disclosed in an opinion paragraph unless the
auditor does not concur and wishes to qualify the opinion. In such case an explanatory paragraph would
precede the opinion paragraph and the opinion paragraph would be qualified.

NEW QUESTION: 2
Overview
Application Overview
Contoso, Ltd., is the developer of an enterprise resource planning (ERP) application.
Contoso is designing a new version of the ERP application. The previous version of the ERP application
used SQL Server 2008 R2.
The new version will use SQL Server 2014.
The ERP application relies on an import process to load supplier data. The import process updates
thousands of rows simultaneously, requires exclusive access to the database, and runs daily.
You receive several support calls reporting unexpected behavior in the ERP application. After analyzing
the calls, you conclude that users made changes directly to the tables in the database.
Tables
The current database schema contains a table named OrderDetails.
The OrderDetails table contains information about the items sold for each purchase order. OrderDetails
stores the product ID, quantities, and discounts applied to each product in a purchase order.
The product price is stored in a table named Products. The Products table was defined by using the
SQL_Latin1_General_CP1_CI_AS collation.
A column named ProductName was created by using the varchar data type. The database contains a
table named Orders.
Orders contains all of the purchase orders from the last 12 months. Purchase orders that are older than
12 months are stored in a table named OrdersOld.
The previous version of the ERP application relied on table-level security.
Stored Procedures
The current version of the database contains stored procedures that change two tables. The following
shows the relevant portions of the two stored procedures:

Customer Problems
Installation Issues
The current version of the ERP application requires that several SQL Server logins be set up to function
correctly. Most customers set up the ERP application in multiple locations and must create logins multiple
times.
Index Fragmentation Issues
Customers discover that clustered indexes often are fragmented. To resolve this issue, the customers
defragment the indexes more frequently. All of the tables affected by fragmentation have the following
columns that are used as the clustered index key:

Backup Issues
Customers who have large amounts of historical purchase order data report that backup time is
unacceptable.
Search Issues
Users report that when they search product names, the search results exclude product names that contain
accents, unless the search string includes the accent.
Missing Data Issues
Customers report that when they make a price change in the Products table, they cannot retrieve the price
that the item was sold for in previous orders.
Query Performance Issues
Customers report that query performance degrades very quickly. Additionally, the customers report that
users cannot run queries when SQL Server runs maintenance tasks. Import Issues During the monthly
import process, database administrators receive many supports call from users who report that they
cannot access the supplier data. The database administrators want to reduce the amount of time required
to import the data.
Design Requirements
File Storage Requirements
The ERP database stores scanned documents that are larger than 2 MB. These files must only be
accessed through the ERP application. File access must have the best possible read and write
performance.
Data Recovery Requirements
If the import process fails, the database must be returned to its prior state immediately.
Security Requirements
You must provide users with the ability to execute functions within the ERP application, without having
direct access to the underlying tables.
Concurrency Requirements
You must reduce the likelihood of deadlocks occurring when Sales.Prod and Sales.Proc2 execute.
You need to recommend a solution that resolves the missing data issue.
The solution must minimize the amount of development effort. What should you recommend?
A. Normalize the Products table.
B. Denormalize the Products table.
C. Denormalize the OrderDetails table.
D. Normalize the OrderDetails table.
Answer: A
Explanation:
Explanation/Reference:
Explanation:
- Scenario:
- Missing Data Issues
Customers report that when they make a price change in the Products table, they cannot retrieve the price
that the item was sold for in previous orders.
- The current database schema contains a table named OrderDetails. The OrderDetails table contains
information about the items sold for each purchase order. OrderDetails stores the product ID, quantities,
and discounts applied to each product in a purchase order.
The product price is stored in a table named Products.

NEW QUESTION: 3
Given the Terraform configuration below, in which order will the resources be created?
1. resource "aws_instance" "web_server"
2. {
3. ami = "ami-b374d5a5"
4. instance_type = "t2.micro"
5. }
6. resource "aws_eip" "web_server_ip"
7. {
8. vpc = true instance = aws_instance.web_server.id
9. }
A. aws_eip will be created first
aws_instance will be created second
B. aws_eip will be created first
aws_instance will be created second
C. aws_instance will be created first
aws_eip will be created second
D. Resources will be created simultaneously
Answer: C
Explanation:
Explanation
Implicit and Explicit Dependencies
By studying the resource attributes used in interpolation expressions, Terraform can automatically infer when one resource depends on another. In the example above, the reference to aws_instance.web_server.id creates an implicit dependency on the aws_instance named web_server.
Terraform uses this dependency information to determine the correct order in which to create the different resources.
# Example of Implicit Dependency
resource "aws_instance" "web_server" {
ami = "ami-b374d5a5"
instance_type = "t2.micro"
}
resource "aws_eip" "web_server_ip" {
vpc = true
instance = aws_instance.web_server.id
}
In the example above, Terraform knows that the aws_instance must be created before the aws_eip.
Implicit dependencies via interpolation expressions are the primary way to inform Terraform about these relationships, and should be used whenever possible.
Sometimes there are dependencies between resources that are not visible to Terraform. The depends_on argument is accepted by any resource and accepts a list of resources to create explicit dependencies for.
For example, perhaps an application we will run on our EC2 instance expects to use a specific Amazon S3 bucket, but that dependency is configured inside the application code and thus not visible to Terraform. In that case, we can use depends_on to explicitly declare the dependency:
# Example of Explicit Dependency
# New resource for the S3 bucket our application will use.
resource "aws_s3_bucket" "example" {
bucket = "terraform-getting-started-guide"
acl = "private"
}
# Change the aws_instance we declared earlier to now include "depends_on" resource "aws_instance" "example" { ami = "ami-2757f631" instance_type = "t2.micro"
# Tells Terraform that this EC2 instance must be created only after the
# S3 bucket has been created.
depends_on = [aws_s3_bucket.example]
}
https://learn.hashicorp.com/terraform/getting-started/dependencies.html

NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You need to recommend a solution to meet the technical requirement for mailbox data retention.
Solution: Create a personal tag and add the tag to a new retention policy. Assign the retention policy to the mailboxes.
Does this meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation/Reference:
Explanation:
/All Exchange Online mailbox data must be retained for 18 months (540 days) and then moved to a user's archive mailbox.
Assigning a retention policy that includes a personal tag will allow users to change the retention period. It will therefore not meet the goal.
References: https://technet.microsoft.com/en-us/library/dd297955(v=exchg.160).aspx#RT