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>> Data-Con-101 Exam Actual Questions <<
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NEW QUESTION # 130
A customer has a calculated insight about lifetime value.
What does the consultant need to be aware of if the calculated insight.
needs to be modified?
Answer: B
Explanation:
A calculated insight is a multidimensional metric that is defined and calculated from data using SQL expressions. A calculated insight can include dimensions and measures. Dimensions are the fields that are used to group or filter the data, such as customer ID, product category, or region. Measures are the fields that are used to perform calculations or aggregations, such as revenue, quantity, or average order value. A calculated insight can be modified by editing the SQL expression or changing the data space. However, the consultant needs to be aware of the following limitations and considerations when modifying a calculated insight12:
Existing dimensions cannot be removed. If a dimension is removed from the SQL expression, the calculated insight will fail to run and display an error message. This is because the dimension is used to create the primary key for the calculated insight object, and removing it will cause a conflict with the existing data.
Therefore, the correct answer is B.
New dimensions can be added. If a dimension is added to the SQL expression, the calculated insight will run and create a new field for the dimension in the calculated insight object. However, the consultant should be careful not to add too many dimensions, as this can affect the performance and usability of the calculated insight.
Existing measures can be removed. If a measure is removed from the SQL expression, the calculated insight will run and delete the field for the measure from the calculated insight object. However, the consultant should be aware that removing a measure can affect the existing segments or activations that use the calculated insight.
New measures can be added. If a measure is added to the SQL expression, the calculated insight will run and create a new field for the measure in the calculated insight object. However, the consultant should be careful not to add too many measures, as this can affect the performance and usability of the calculated insight. References: Calculated Insights, Calculated Insights in a Data Space.
NEW QUESTION # 131
Northern Trail Outfitters (NTO) is getting ready to start ingesting its CRM data into Data Cloud.
While setting up the connector, which type of refresh should NTO expect when the data stream is deployed for the first time?
Answer: C
Explanation:
Data Stream Deployment: When setting up a data stream in Salesforce Data Cloud, the initial deployment requires a comprehensive data load.
Types of Refreshes:
Incremental Refresh: Only updates with new or changed data since the last refresh.
Manual Refresh: Requires a user to manually initiate the data load.
Partial Refresh: Only a subset of the data is refreshed.
Full Refresh: Loads the entire dataset into the system.
First-Time Deployment: For the initial deployment of a data stream, a full refresh is necessary to ensure all data from the source system is ingested into Salesforce Data Cloud.
References:
Salesforce Documentation: Data Stream Setup
Salesforce Data Cloud Guide
NEW QUESTION # 132
A customer has two Data Cloud orgs. A new configuration has been completed and tested for an Amazon S3 data stream and its mappings in one of the Data Cloud orgs.
What is recommended to package and promote this configuration to the customer's second org?
Answer: C
Explanation:
Data Cloud Configuration Promotion: When managing configurations across multiple Salesforce Data Cloud orgs, it's essential to use tools that ensure consistency and accuracy in the promotion process.
Data Kits: Salesforce Data Cloud allows users to package and promote configurations using data kits. These kits encapsulate data stream definitions, mappings, and other configuration elements into a portable format.
Process:
Create a data kit in the source org that includes the Amazon S3 data stream configuration and mappings.
Export the data kit from the source org.
Import the data kit into the target org, ensuring that all configurations are transferred accurately.
Advantages: Using data kits simplifies the migration process, reduces the risk of configuration errors, and ensures that all settings and mappings are consistently applied in the new org.
References:
Salesforce Data Cloud Developer Guide
Salesforce Data Cloud Packaging
NEW QUESTION # 133
A consultant is connecting sales order data to Data Cloud and considers whether to use the Profile, Engagement, or Other categories to map the DLO. The consultant chooses to map the DLO called Order- Headers to the Sales Order DMO using the Engagement category.
What is the impact of this action on future mappings?
Answer: C
Explanation:
Data Lake Objects (DLOs) and Data Model Objects (DMOs): In Salesforce Data Cloud, DLOs are mapped to DMOs to organize and structure data. Categories like Profile, Engagement, and Other define how these mappings are used.
Engagement Category: Mapping a DLO to the Engagement category indicates that the data is related to customer interactions and activities.
Impact on Future Mappings:
Engagement Category Restriction: When a DLO like Order-Headers is mapped to the Sales Order DMO under the Engagement category, future mappings of the Sales Order DMO are restricted to Engagement category DLOs.
Category Assignment: The Sales Order DMO is assigned to the Engagement category, meaning only DLOs categorized as Engagement can be mapped to it in the future.
Benefits:
Consistency: Ensures consistent data categorization and usage, aligning data with its intended purpose.
Accuracy: Helps in maintaining the integrity of data mapping and ensures that engagement-related data is accurately captured and utilized.
References:
Salesforce Data Cloud Mapping
Salesforce Data Cloud Categories
NEW QUESTION # 134
Cloud Kicks wants to be able to build a segment of customers who have visited its website within the previous 7 days.
Which filter operator on the Engagement Date field fits this use case?
Answer: A
Explanation:
The filter operator Last Number of Days allows you to filter on date fields using a relative date range that specifies the number of days before today. For example, you can use this operator to filter on customers who have visited your website in the last 7 days, or the last 30 days, or any number of days you want. This operator is useful for creating dynamic segments that update automatically based on the current date12. References:
Relative Date Filter Reference
Create Filtered Segments
NEW QUESTION # 135
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