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| Section | Weight | Objectives |
|---|---|---|
| Data Cloud Setup and Administration | 12% | - Permissions, permission sets, and org settings - Data streams, data bundles, and data spaces - Administration tools: reports, dashboards, flows, packaging - Data exploration and diagnostics: Explorer tools, APIs |
| Act on Data | 18% | - Data actions and requirements - Activation concepts and use cases - Troubleshooting activation issues - Attributes, related attributes, and timing dependencies |
| Segmentation and Insights | 18% | - Segment creation, maintenance, and membership analysis - Calculated vs. streaming insights - Segmentation concepts and business scenarios |
| Data Cloud Overview | 18% | - Architecture, dependencies, and lifecycle - Data ethics and responsible usage principles - Core functions, terminology, and business value - Common enterprise use cases |
| Identity Resolution | 14% | - Reconciliation rules and data unification - Unified identity outcomes and use cases - Matching rules and application |
| Data Ingestion and Modeling | 20% | - Transformation and data mapping capabilities - Validation and inspection of ingested data - Ingestion from various source systems - Data modeling best practices aligned with identity resolution |
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NEW QUESTION # 64
Cumulus Financial is experiencing delays in publishing multiple segments simultaneously. The company wants to avoid reducing the frequency at which segments are published, while retaining the same segments in place today.
Which action should a consultant take to alleviate this issue?
Answer: A
Explanation:
Cumulus Financial is experiencing delays in publishing multiple segments simultaneously and wants to avoid reducing the frequency of segment publishing while retaining the same segments. The best solution is to increase the Data Cloud segmentation concurrency limit . Here's why:
Understanding the Issue
The company is publishing multiple segments simultaneously, leading to delays.
Reducing the frequency or number of segments is not an option, as these are business-critical requirements.
Why Increase the Segmentation Concurrency Limit?
Segmentation Concurrency Limit :
Salesforce Data Cloud has a default limit on the number of segments that can be processed concurrently.
If multiple segments are being published at the same time, exceeding this limit can cause delays.
Solution Approach :
Increasing the segmentation concurrency limit allows more segments to be processed simultaneously without delays.
This ensures that all segments are published on time without reducing the frequency or removing existing segments.
Steps to Resolve the Issue
Step 1: Check Current Concurrency Limit
Navigate to Setup > Data Cloud Settings and review the current segmentation concurrency limit.
Step 2: Request an Increase
Contact Salesforce Support or your Salesforce Account Executive to request an increase in the segmentation concurrency limit.
Step 3: Monitor Performance
After increasing the limit, monitor segment publishing to ensure delays are resolved.
Why Not Other Options?
A). Enable rapid segment publishing to all to segment to reduce generation time :Rapid segment publishing is designed for faster generation but does not address concurrency issues when multiple segments are being published simultaneously.
B). Reduce the number of segments being published :This contradicts the requirement to retain the same segments and avoid reducing frequency.
D). Adjust the publish schedule start time of each segment to prevent overlapping processes :While staggering schedules may help, it does not fully resolve the issue of delays caused by concurrency limits.
Conclusion
By increasing the Data Cloud segmentation concurrency limit , Cumulus Financial can alleviate delays in publishing multiple segments simultaneously while meeting business requirements.
NEW QUESTION # 65
A user wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV).
Which sequence of data model object (DMO) joins is necessary within the calculated Insight to enable this calculation?
Answer: D
Explanation:
To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the sequence of data model object (DMO) joins that is necessary within the calculated Insight is Unified Individual > Unified Link Individual > Sales Order. This is because the Unified Individual DMO represents the unified profile of an individual or entity that is created by identity resolution1. The Unified Link Individual DMO represents the link between a unified individual and an individual from a source system2. The Sales Order DMO represents the sales order information from a source system3. By joining these three DMOs, you can calculate the LTV of a unified individual based on the sales order data from different source systems. The other options are incorrect because they do not join the correct DMOs to enable the LTV calculation. Option B is incorrect because the Individual DMO represents the source profile of an individual or entity from a source system, not the unified profile4. Option C is incorrect because the join order is reversed, and you need to start with the Unified Individual DMO to identify the unified profile. Option D is incorrect because it is missing the Unified Link Individual DMO, which is needed to link the unified profile with the source profile. References: Unified Individual Data Model Object, Unified Link Individual Data Model Object, Sales Order Data Model Object, Individual Data Model Object
NEW QUESTION # 66
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: C
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 # 67
Northern Trail Outfitters (NTD) creates a calculated insight to compute recency, frequency, monetary {RFM) scores on its unified individuals. NTO then creates a segment based on these scores that it activates to a Marketing Cloud activation target.
Which two actions are required when configuring the activation?
Choose 2 answers
Answer: A,B
Explanation:
To configure an activation to a Marketing Cloud activation target, you need to choose a segment and select contact points. Choosing a segment allows you to specify which unified individuals you want to activate.
Selecting contact points allows you to map the attributes from the segment to the fields in the Marketing Cloud data extension. You do not need to add additional attributes or add the calculated insight in the activation, as these are already part of the segment definition. References: Create a Marketing Cloud Activation Target; Types of Data Targets in Data Cloud
NEW QUESTION # 68
Which statement about Data Cloud's Web and Mobile Application Connector is true?
Answer: D
Explanation:
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the TSE. References: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream
NEW QUESTION # 69
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