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| Section | Objectives |
|---|---|
| Topic 1: Implement security and governance | - Field and record security
|
| Topic 2: Configure Dynamics 365 Customer Experience applications | - Customize user experience
|
| Topic 3: Manage Dataverse and customer data | - Data management
|
| Topic 4: Configure automation and integrations | - Integration scenarios
|
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NEW QUESTION # 88
You are working with your customer to configure duplicate detection across Leads and Accounts.
The rule must:
* find possible Contacts in the system that match the Lead that you are creating based on an exact match of both first and last name.
* exclude Inactive Contacts when presenting potential duplicates.
You need to create a new duplicate detection rule based on these requirements.
Which three actions should you perform? Each correct answer presents part of the solution. Choose three.
NOTE: Each correct selection is worth one point.
Answer: C,D,E
NEW QUESTION # 89
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.
A company's IT department has a .CSV file stored on one of their Shared Documents folders within their Microsoft SharePoint sites. The data from the .CSV file is ingested into Dynamics 365 Customer Insights - Data.
The file contains a row header and columns of different types, such as quantities and prices. The file also contains some rows with a high proportion of nulls.
You need to clean and transform the data in Customer Insights - Data to be ready for unification.
Solution: Define column types to be appropriate field types and name the query. Create a full name and full address columns by merging the appropriate columns, if they exist. Select Next and your data is now ready for unification.
Does this meet the goal?
Answer: B
Explanation:
Correct:
* Transform the first row to be used as headers. Define column types to be the appropriate field types and name the query. Create a full name and full address columns by merging the appropriate columns if they exist. Select Next and your data is now ready for unification.
The proposed solution effectively prepares the data for unification in Dynamics 365 Customer Insights - Data.
Here's how each step contributes to meeting the goal:
Transform the first row to be used as headers: This step is necessary to define the column names, which is critical for accurate data interpretation.
Define column types to be the appropriate field types: Specifying the correct data types for each column ensures that the data will be processed correctly during unification, maintaining data integrity.
Create a full name and full address columns by merging the appropriate columns if they exist: This step enhances the dataset by consolidating relevant information into single columns, which can simplify data usage and improve data quality. Merging columns helps ensure that users can easily access essential information without navigating through multiple fields.
Select Next: This indicates that the data transformation steps are completed and the dataset is ready for the unification process.
Incorrect:
* Define column types to be appropriate field types and name the query. Create a full name and full address columns by merging the appropriate columns, if they exist. Select Next and your data is now ready for unification.
Does not address the problem with null values.
* Remove any rows where the primary key is missing, delete any leading or trailing zeros on the primary key, and name the query. Select Next and your data is now ready for unification.
Problem not related to the primary key.
* Transform the first row to be used as headers, and remove any special characters or spaces from header row.
Remove rows with missing primary keys and name the query. Select Next and your data is now ready for unification.
Does not address the problem with null values.
* Transform the first row to be used as headers, define column types to be the appropriate field types and name the query. Select Next and your data is now ready for unification.
Solution removes all rows with null values, which can lead to significant data loss, especially if those rows contain important information.
It may compromise data quality by eliminating rows, which can impact analysis and insights.
* Transform the first row to be used as headers, remove rows that contain null values, and name the query.
Select Next and your data is now ready for unification.
While the solution includes transforming the first row to be used as headers and naming the query, the step of removing rows that contain null values is problematic.
Removing all rows with null values can lead to significant data loss, particularly if those rows contain relevant information.
NEW QUESTION # 90
A marketing user wants to target two groups of customers:
1. All customers that live in Paris.
2. All customers that have made more than ten online purchases.
You decide to meet this requirement by making quick segments.
Which two options should you use as the base in the quick segments? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
* All customers that live in Paris.
Customer profile data has address information.
* All customers that have made more than ten online purchases.
Incorrect:
Not Data tables [Not available for Quick Segments]
Not Enrichments [Not available for Quick Segments]
Note:
Quick segments let you build simple segments with a single operator quickly for faster insights.
Quick segments are only supported in environments for individual customers.
Create a new segment with quick segments
1. Go to Insights > Segments.
2. Select New > Create from.
Select the Profiles option to build a segment that is based on the unified customer table.
Select the Measures option to build a segment around measures you have previously created.
Select the Insights option to build a segment around one of the output tables you generated using either the Predictions or Custom Models capabilities.
3. In the New quick segment dialog box, select an attribute from the Field dropdown.
Etc.
NEW QUESTION # 91
A company manually assigns leads to salespeople.
The sales manager requires automated lead assignment rules. An administrator enables the feature. However, you are unable to access the Assignment rules area.
You need to request access from the administrator.
Which security role should you request?
Answer: B
Explanation:
Dynamics 365 Sales, Create and activate assignment rules
You can create and manage sequences and assignment rules through navigating to 'Personal Settings' area if users have sequence manager role.
Reference:
https://community.dynamics.com/forums/thread/details/?threadid=36a7818d-0ff5-48c8-a9ea-f9b25d8d9e7e
NEW QUESTION # 92
One of the data sources being ingested into Dynamics 365 Customer Insights - Data is Microsoft Dataverse.
During the unification process, you need to identify the primary key.
Which three data types can you use as a primary key attribute? Each correct answer presents a complete solution. Choose three. NOTE: Each correct selection is worth one point.
Answer: B,C,D
Explanation:
In Dynamics 365 Customer Insights - Data, primary key attributes must uniquely identify records and be consistent across the data source.
Whole Number and GUID are commonly used data types for primary keys because they can uniquely identify records and are natively supported for primary keys in databases.
String can also be used as a primary key if it uniquely identifies each record (e.g., an email address).
Integer and Boolean are generally not used as primary keys in Customer Insights because they may not provide unique identifiers suitable for all scenarios.
Reference: Microsoft Documentation - Configure Primary Key in Dynamics 365 Customer Insights
NEW QUESTION # 93
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