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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Segmentation and Insights | 18% | - AI-powered insights and analysis - Calculated vs streaming insights - Segment creation, configuration, and maintenance |
| Topic 2: Data Ingestion and Modeling | 20% | - Ingestion methods, connectors, and transformation - Data mapping, validation, and quality best practices - Customer 360 data model and schema design |
| Topic 3: Setup and Administration | 13% | - Data streams, data spaces, and governance - Permissions, settings, and security configuration - Monitoring, reporting, and tools (Data Explorer, APIs) |
| Topic 4: 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 5: Act on Data / Activation | 18% | - Troubleshooting activation issues and dependencies - Data actions and integration with Salesforce products - Activation types and use cases |
| Topic 6: Identity Resolution and Harmonization | 14% | - Identity graphs and data unification - Matching rules (deterministic / probabilistic) - Reconciliation and result analysis |
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NEW QUESTION # 93
A Data 360 Consultant for Northern Trail Outfitters is observing Identity Resolution processing metrics. The consultant notices that the volume of source profiles processed in the most recent batch is less than the total volume of source profiles. What is the most likely mechanism that causes source profiles to be skipped during Identity Resolution processing?
Answer: D
Explanation:
The identity logic is about linking source profiles safely, then choosing the best surviving values for the unified profile. A profile is only processed if a pre-processing step confirms a change in its data since the last processing run. is appropriate because identity resolution needs reliable match inputs, qualified identifiers, and controlled reconciliation. It is not just deduplication; it is a rules-driven process that connects source records into a trusted unified profile. 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.
NEW QUESTION # 94
Cumulus Financial is currently using Data Cloud and ingesting transactional data from its backend system via an S3 Connector in upsert mode. During the initial setup six months ago, the company created a formula field in Data Cloud to create a custom classification. It now needs to update this formula to account for more classifications.
What should the consultant keep in mind with regard to formula field updates when using the S3 Connector?
Answer: C
NEW QUESTION # 95
A consultant is reviewing a recent activation using engagement-based related attributes but is not seeing any related attributes in their payload for the majority of their segment members.
Which two areas should the consultant review to help troubleshoot this issue?
Choose 2 answers
Answer: C,D
Explanation:
Engagement-based related attributes are attributes that describe the interactions of a person with an email message, such as opens, clicks, unsubscribes, etc. These attributes are stored in the Engagement data model object (DMO) and can be added to an activation to send more personalized communications. However, there are some considerations and limitations when using engagement-based related attributes, such as:
For engagement data, activation supports a 90-day lookback window. This means that only the attributes from the engagement events that occurred within the last 90 days are considered for activation. Any records outside of this window are not included in the activation payload. Therefore, the consultant should review the event time of the related engagement events and make sure they are within the lookback window.
The correct path to the related attributes must be selected for the activation. A path is a sequence of DMOs that are connected by relationships in the data model. For example, the path from Individual to Engagement is Individual -> Email -> Engagement. The path determines which related attributes are available for activation and how they are filtered. Therefore, the consultant should review the path selection and make sure it matches the desired related attributes and filters.
The other two options are not relevant for this issue. The activations can reference segments that segment on profile data rather than engagement data, as long as the activation target supports related attributes. The activated profiles do not need to have a Unified Contact Point, which is a unique identifier for a person across different data sources, to activate engagement-based related attributes. References: Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object
NEW QUESTION # 96
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 # 97
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?
Answer: B
NEW QUESTION # 98
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