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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Delivery and Implementation | 16% | - Integration and deployment best practices - Feature assessment: out-of-the-box vs custom - Solution validation and optimization |
| Topic 2: Planning and Design | 60% | - Order capture, quoting and fulfillment design - Design scalable product catalog and data model - Migration strategy and data quality - Asset management and MACD flows - Sprint planning and story prioritization |
| Topic 3: Discovery | 24% | - Analyze requirements and constraints - Assess customer IT ecosystem and architecture - Define KPIs and business objectives |
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NEW QUESTION # 10
A company is selling voice products to business customers. The offer allows customers to select devices of various models. The product modeler intends to create a phone add-on product specification with voice offers with a cardinality that allows up to 700. Which of the three statement are valid regarding the product model in this scenario?
Answer: A,B,C
Explanation:
EPC supports hierarchical product modeling, but very high child cardinalities can create substantial runtime cost. Hundreds of instantiated child products increase cart validation, MACD comparison, decomposition volume, generated Fulfillment Request Lines, heap use, and orchestration-plan composition. A technically supported catalog structure can therefore become operationally inefficient or exceed transaction limits at its maximum configured size. The recommended configuration follows the native Communications Cloud responsibility boundary: catalog and CPQ determine the commercial request, while Order Management, OmniStudio, or the relevant platform service performs the downstream processing required by the use case.
The correct conclusion is not that hierarchy is unsupported; it is that product-model scale must be tested against CPQ and Order Management limits. Large cardinalities should be justified and modeled with performance consequences in mind. Avoiding duplicate logic is important because repeated rules across catalog, integration, and orchestration layers quickly become inconsistent as products evolve. The selected approach keeps the authoritative data in the correct object model, supports later lifecycle operations, and minimizes additional processing or manual intervention. It should be implemented declaratively wherever the platform feature can express the requirement, with customization reserved only for behavior that genuinely falls outside the supported framework.
Study Guide Reference:EPC hierarchy; cardinality; MACD performance; decomposition scalability; governor limits.
NEW QUESTION # 11
Exclusive VPN corporation wants to automate their offering of complete B2B services and realizes that their order can be very large and will from time to time violate Order Management's Document size limits. Which two techniques can a consultant use to migrate the risk of large order hitting governor limits?
Answer: A,D
NEW QUESTION # 12
Universal Containers is using Communications Cloud for their B2B use cases. They have an integration with a legacy stack that will handle network provisioning and billing. As part of their Order Management process they have to send the customer data to the legacy app, which in turn provisions billing. What should a Consultant recommend to make this callout easier to configure, easier to maintain, and performant?
Answer: D
Explanation:
Customer information that is needed in a downstream callout but is not itself a technical product should be modeled on the Order or related transactional context and extracted into the request payload through standard mapping. This keeps customer master/transaction data separate from the technical catalog and makes the integration easier to understand and maintain. In a Communications Cloud implementation, this pattern provides the cleanest balance of reuse, governance, and runtime efficiency. Creating artificial technical products or multi-select product attributes just to transport customer data pollutes the fulfillment model, while a custom adapter adds query and code complexity that standard request mapping can avoid. The alternative designs either introduce unnecessary coupling, fail to preserve the required lifecycle state, or move standard platform behavior into bespoke code. Keeping the solution within the documented product, pricing, migration, or orchestration framework also gives operations teams clearer monitoring and recovery paths. For production readiness, the configuration should be exercised with realistic data volumes and representative MACD scenarios so that the behavior remains correct after the initial sale and throughout subsequent service changes.
Study Guide Reference:Order-level integration data; Callout payloads; Data Mappers; technical-product modeling boundaries.
NEW QUESTION # 13
During the discovery phase a consultant learns that provisioning the internet service requires multiple steps of integration. The first step returns as identifier that is required for the second steps, but is meaningless in ensuring steps afterwards. How should the consultant implement this requirement in Order Management with the least amount of configurations?
Answer: A
NEW QUESTION # 14
Universal containers is a communication service provider using communication cloud. A member of UC ' s legacy- system IT team has provided a consultant with an extract of all the existing products from the legacy system and asked the consultant to migrate the data to communication cloud which two question should the consultant ask in this scenario to clarify the data migration strategy?
Answer: C,D
Explanation:
Catalog migration should begin with rationalization rather than a mechanical copy of every legacy SKU or offer. The consultant should identify which products are still actively sold and determine whether duplicate or near-duplicate products can be consolidated using object types, attributes, specifications, and reusable structures. This reduces the amount of configuration that must be priced, governed, tested, and maintained after migration. The practical benefit is that the solution remains scalable and deterministic as order volume or catalog complexity grows. Simply preserving every legacy record as inactive or bundling duplicates together does not remove the underlying catalog complexity. The target EPC should reflect the desired future-state product model, not reproduce historical proliferation. A design that relies on unnecessary custom code, duplicated catalog records, or manual recovery may work for a small pilot but becomes difficult to operate at telecommunications scale. The standard Salesforce Industries capability provides the expected lifecycle hooks, data ownership, and processing semantics needed for production support. Configuration should therefore be kept as close as possible to the managed feature set, with clear dependencies and explicit conditions so that each transaction produces a predictable commercial and technical result.
Study Guide Reference:Enterprise Product Catalog; product rationalization; Object Types; attributes; migration scope.
NEW QUESTION # 15
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