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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Act on Data / Activation | 18% | - Data actions and integration with Salesforce products - Activation types and use cases - Troubleshooting activation issues and dependencies |
| Topic 2: Segmentation and Insights | 18% | - Calculated vs streaming insights - AI-powered insights and analysis - Segment creation, configuration, and maintenance |
| Topic 3: Identity Resolution and Harmonization | 14% | - Identity graphs and data unification - Matching rules (deterministic / probabilistic) - Reconciliation and result analysis |
| Topic 4: Setup and Administration | 13% | - Permissions, settings, and security configuration - Data streams, data spaces, and governance - Monitoring, reporting, and tools (Data Explorer, APIs) |
| Topic 5: Solution Positioning / Overview | 14% | - Data 360 / Data Cloud terminology and business value - Common use cases and data ethics principles - Role in AI and predictive capabilities |
| Topic 6: Data Ingestion and Modeling | 20% | - Data mapping, validation, and quality best practices - Customer 360 data model and schema design - Ingestion methods, connectors, and transformation |
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NEW QUESTION # 76
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?
Answer: C
Explanation:
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign.
The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules
NEW QUESTION # 77
A healthcare client wants to make use of identity resolution, but does not want to risk unifying profiles that may share certain personally identifying information (PII).
Which matching rule criteria should a consultant recommend for the most accurate matching results?
Answer: A
Explanation:
Explanation
Identity resolution is the process of linking data from different sources into a unified profile of a customer or an individual. Identity resolution uses matching rules to compare the attributes of different records and determine if they belong to the same person. Matching rules can be based on exact or fuzzy matching of various attributes, such as name, email, phone, address, or custom identifiers. A healthcare client who wants to use identity resolution, but does not want to risk unifying profiles that may share certain personally identifying information (PII), such as name or email, should use a matching rule criteria that is based on a unique and reliable identifier that is specific to the healthcare domain. One such identifier is the patient ID, which is a unique number assigned to each patient by a healthcare provider or system. By using the party identification on patient ID as a matching rule criteria, the healthcare client can ensure that only records that have the same patient ID are matched and unified, and avoid false positives or false negatives that may occur due to common or similar names or emails. The party identification on patient ID is also a secure and compliant way of handling sensitive healthcare data, as it does not expose or share any PII that may be subject to data protection regulations or standards. References: Configure Identity Resolution Rulesets, A framework of identity resolution: evaluating identity attributes and methods
NEW QUESTION # 78
Northern Trail Outfitters unifies individuals in its Data Cloud instance.
Which three features ca e consultant use to validate the data on a unified profile?
Choose 3 answers
Answer: A,C,D
Explanation:
To validate the data on a unified profile, the consultant can use the following features:
* Identity Resolution: This feature allows the consultant to view and edit the identity resolution rulesets that determine how individuals are unified from different data sources1.
* Data Explorer: This feature allows the consultant to browse and filter the unified profiles and view their attributes, segments, and activities2.
* Profile Explorer: This feature allows the consultant to drill down into a specific unified profile and view its details, such as source records, identity graph, calculated insights, and data actions3. References:
* 1: Identity Resolution in Data Cloud
* 2: Data Explorer in Data Cloud
* 3: Profile Explorer in Data Cloud
NEW QUESTION # 79
Northern Trail Outfitters wants to compute recency, frequency, monetary (RFM) scores on its unified individuals in order to use it in Marketing Cloud Engagement. What is the best way to achieve this goal?
Answer: B
Explanation:
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Include the Calculated Insight attribute in activation. works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
NEW QUESTION # 80
A Data 360 Consultant wants to perform aggregations in 15-minute windows on data collected via the Interactions SDK or Mobile SDK. Which method should the consultant use?
Answer: A
Explanation:
The core Data 360 principle is harmonization: bring data from multiple systems into a governed model that business teams can use consistently. Streaming insight is the strongest answer because Data 360 is designed to unify, harmonize, and activate customer and business data across systems. The platform is not merely a dashboard, archive, or point solution. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
NEW QUESTION # 81
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