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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Act on Data | 18% | - Process automation and triggering - Activation concepts and use cases - Attribute usage and management - Troubleshooting activations |
| Topic 2: Identity Resolution | 14% | - Unified profile creation - Identity use cases - Conflict resolution - Matching and reconciliation rules |
| Topic 3: Data Ingestion and Modeling | 20% | - Transformation and mapping - Data validation and inspection - Data modeling best practices - Ingestion from various sources |
| Topic 4: Segmentation and Insights | 18% | - Insight implementation - Calculated vs streaming insights - Segment creation and configuration - Segment membership analysis |
| Topic 5: Data Cloud Setup and Administration | 12% | - Monitoring and maintenance tools - Data spaces and configuration - Data streams and data bundles - Permissions and access control |
| Topic 6: Data Cloud Overview | 18% | - Architecture and ecosystem - Core concepts and terminology - Business value and use cases |
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NEW QUESTION # 168
A customer wants to use the transactional data from their data warehouse in Data Cloud. They are only able to export the data via a SFTP site. What are two recommended ways to bring this data into Data Cloud?
Answer: B,C
Explanation:
These two options are recommended ways to bring transactional data from a data warehouse into Data Cloud via a SFTP site. You can use the Cloud Storage Connector to ingest files from Google Cloud Storage or Amazon S3 buckets into Data Cloud.
References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_google_cloud_storage.htm&type
NEW QUESTION # 169
What does the Ignore Empty Value option do in identity resolution?
Answer: A
Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Data Cloud Identity Resolution Reconciliation Rule Input
Configure Identity Resolution Rulesets
Data and Identity in Data Cloud
NEW QUESTION # 170
A customer wants to create segments of users based on their Customer Lifetime Value.
However, the source data that will be brought into Data Cloud does not include that key performance indicator (KPI).
Which sequence of steps should the consultant follow to achieve this requirement?
Answer: C
Explanation:
To create segments of users based on their Customer Lifetime Value (CLV), the sequence of steps that the consultant should follow is Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation. This is because the first step is to ingest the source data into Data Cloud using data streams1. The second step is to map the source data to the data model, which defines the structure and attributes of the data2. The third step is to create a calculated insight, which is a derived attribute that is computed based on the source or unified data3. In this case, the calculated insight would be the CLV, which can be calculated using a formula or a query based on the sales order data4. The fourth step is to use the calculated insight in segmentation, which is the process of creating groups of individuals or entities based on their attributes and behaviors. By using the CLV calculated insight, the consultant can segment the users by their predicted revenue from the lifespan of their relationship with the brand. The other options are incorrect because they do not follow the correct sequence of steps to achieve the requirement. Option B is incorrect because it is not possible to create a calculated insight before ingesting and mapping the data, as the calculated insight depends on the data model objects3. Option C is incorrect because it is not possible to create a calculated insight before mapping the data, as the calculated insight depends on the data model objects3. Option D is incorrect because it is not recommended to create a calculated insight before mapping the data, as the calculated insight may not reflect the correct data model structure and attributes3. References: Data Streams Overview, Data Model Objects Overview, Calculated Insights Overview, Calculating Customer Lifetime Value (CLV) With Salesforce, [Segmentation Overview]
NEW QUESTION # 171
A user needs permissions to access Data Cloud to create, manage, and publish segments. However, the user should not be allowed to create reports or manage data sources. Which permission set should an administrator assign?
Answer: D
Explanation:
This permission set should be assigned to a user who needs permissions to access Data Cloud to create, manage, and publish segments, but not to create reports or manage data sources. This permission set allows the user to create and edit segments, calculated insights, streaming insights, and activations, but not to access data streams, data model, identity resolution, or reports. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_permission_sets.htm&type=5
NEW QUESTION # 172
A consultant is working in a customer's Data Cloud org and is asked to delete the existing identity resolution ruleset.
Which two impacts should the consultant communicate as a result of this action?
Choose 2 answers
Answer: A,D
Explanation:
Deleting an identity resolution ruleset has two major impacts that the consultant should communicate to the customer. First, it will permanently remove all unified customer data that was created by the ruleset, meaning that the unified profiles and their attributes will no longer be available in Data Cloud1. Second, it will eliminate dependencies on data model objects that were used by the ruleset, meaning that the data model objects can be modified or deleted without affecting the ruleset1. These impacts can have significant consequences for the customer's data quality, segmentation, activation, and analytics, so the consultant should advise the customer to carefully consider the implications of deleting a ruleset before proceeding. The other options are incorrect because they are not impacts of deleting a ruleset. Option A is incorrect because deleting a ruleset will not remove all individual data, but only the unified customer data. The individual data from the source systems will still be available in Data Cloud1. Option D is incorrect because deleting a ruleset will not remove all source profile data, but only the unified customer data. The source profile data from the data streams will still be available in Data Cloud1. References: Delete an Identity Resolution Ruleset
NEW QUESTION # 173
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