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| Section | Weight | Objectives |
|---|---|---|
| Setup and Administration | 13% | - Data streams, data spaces, and governance - Permissions, settings, and security configuration - Monitoring, reporting, and tools (Data Explorer, APIs) |
| Segmentation and Insights | 18% | - AI-powered insights and analysis - Calculated vs streaming insights - Segment creation, configuration, and maintenance |
| Identity Resolution and Harmonization | 14% | - Matching rules (deterministic / probabilistic) - Reconciliation and result analysis - Identity graphs and data unification |
| Act on Data / Activation | 18% | - Troubleshooting activation issues and dependencies - Activation types and use cases - Data actions and integration with Salesforce products |
| Solution Positioning / Overview | 14% | - Common use cases and data ethics principles - Data 360 / Data Cloud terminology and business value - Role in AI and predictive capabilities |
| Data Ingestion and Modeling | 20% | - Ingestion methods, connectors, and transformation - Customer 360 data model and schema design - Data mapping, validation, and quality best practices |
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NEW QUESTION # 18
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: C
Explanation:
The modeling decision should make the data understandable, reusable, and correctly related before segmentation or activation depends on it. Sales Order > Individual > Unified Individual fits because Data 360 depends on mappings and relationships between data lake objects and data model objects. Correct modeling lets the same attribute mean the same thing across source systems and prevents downstream users from building logic on ambiguous fields. 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 # 19
A marketing manager at Northern Trail Outfitters wants to Improve marketing return on investment (ROI) by tapping into Insights from Data Cloud Segment Intelligence.
Which permission set does a user need to set this up?
Answer: A
NEW QUESTION # 20
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations.
Which configuration change should a consultant consider in order to increase the consolidation rate?
Answer: D
NEW QUESTION # 21
A consultant is setting up a data stream with transactional data,
Which field typeshould the consultant choose toensure that leading
zeros in the purchase order number are preserved?
Answer: D
Explanation:
Explanation
The field type Text should be chosen to ensure that leading zeros in the purchase order number are preserved.
This is because text fields store alphanumeric characters as strings, and do not remove any leading or trailing characters. On the other hand, number, decimal, and serial fields store numeric values as numbers, and automatically remove any leading zeros when displaying or exporting the data123. Therefore, text fields are more suitable for storing data that needs to retain its original format, such as purchase order numbers, zip codes, phone numbers, etc. References:
* Zeros at the start of a field appear to be omitted in Data Exports
* Keep First '0' When Importing a CSV File
* Import and export address fields that begin with a zero or contain a plus symbol
NEW QUESTION # 22
A customer requests that their personal data be deleted. Which action should the Data 360 Consultant take to accommodate this request in Data 360?
Answer: C
Explanation:
The core Data 360 principle is harmonization: bring data from multiple systems into a governed model that business teams can use consistently. Use Consent API to request deletion of the customer ' s information. 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 # 23
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