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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Setup and Administration | 13% | - Data streams, data spaces, and governance - Monitoring, reporting, and tools (Data Explorer, APIs) - Permissions, settings, and security configuration |
| Topic 2: Identity Resolution and Harmonization | 14% | - Matching rules (deterministic / probabilistic) - Reconciliation and result analysis - Identity graphs and data unification |
| Topic 3: Act on Data / Activation | 18% | - Troubleshooting activation issues and dependencies - Data actions and integration with Salesforce products - Activation types and use cases |
| Topic 4: Data Ingestion and Modeling | 20% | - Customer 360 data model and schema design - Ingestion methods, connectors, and transformation - Data mapping, validation, and quality best practices |
| Topic 5: Solution Positioning / Overview | 14% | - Role in AI and predictive capabilities - Common use cases and data ethics principles - Data 360 / Data Cloud terminology and business value |
| Topic 6: Segmentation and Insights | 18% | - AI-powered insights and analysis - Calculated vs streaming insights - Segment creation, configuration, and maintenance |
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NEW QUESTION # 112
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. Reference: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream
NEW QUESTION # 113
A Data 360 Consultant is working with data that is clean and organized. However, the various schemas refer to a person by multiple names-such as user, contact, and subscriber-and need a standard mapping.
Which term describes the process of mapping these different schema points into a standard data model?
Answer: C
Explanation:
Harmonization is the Data 360 modeling process that maps differing source schemas into a consistent, standardized data model. Salesforce explains that source schemas preserved during ingestion are harmonized during data modeling by mapping Data Lake Objects to Data Model Objects in the Customer 360 Data Model.
This enables semantically equivalent source attributes-such as user, subscriber, or contact representations- to be interpreted consistently downstream. Transformation is concerned with changing or deriving data values or structures, while segmentation identifies audiences based on criteria. Unification occurs later through Identity Resolution, where records representing the same person or account are linked into unified profiles.
Because the problem is inconsistent schema terminology rather than duplicate identities, harmonize precisely describes the required process.
NEW QUESTION # 114
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
Answer: C
Explanation:
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines
NEW QUESTION # 115
Which operator should a consultant use to create a segment for a birthday campaign that is evaluated daily?
Answer: C
Explanation:
Explanation
To create a segment for a birthday campaign that is evaluated daily, the consultant should use the Is Anniversary Of operator. This operator compares a date field with the current date and returns true if the month and day are the same, regardless of the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns true. This way, the consultant can create a segment that includes all the customers who have their birthday on the same day as the current date, and the segment will be updated daily with the new birthdays. The other options are not the best operators to use for this purpose because:
* A. The Is Today operator compares a date field with the current date and returns true if the date is the same, including the year. For example, if the date field is 1990-01-01 and the current date is
2023-01-01, the operator returns false. This operator is not suitable for a birthday campaign, as it will only include the customers who were born on the same day and year as the current date, which is very unlikely.
* B. The Is Birthday operator is not a valid operator in Data Cloud. There is no such operator available in the segment canvas or the calculated insight editor.
* C. The Is Between operator compares a date field with a range of dates and returns true if the date is within the range, including the endpoints. For example, if the date field is1990-01-01 and the range is
2022-12-25 to 2023-01-05, the operator returns true. This operator is not suitable for a birthday campaign, as it will only include the customers who have their birthday within a fixed range of dates, and the segment will not be updated daily with the new birthdays.
NEW QUESTION # 116
What does the Ignore Empty Value option do in identity resolution?
Answer: B
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.
References:
* Data Cloud Identity Resolution Reconciliation Rule Input
* Configure Identity Resolution Rulesets
* Data and Identity in Data Cloud
NEW QUESTION # 117
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