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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design | 28% | - Map business requirements to Manufacturing Cloud capabilities - Create technical design documents and architecture plans - Design data models, integrations and security framework - Perform gap analysis and define customization needs |
| Topic 2: Validate and Deploy | 16% | - Support user acceptance testing (UAT) - Perform system testing and performance validation - Execute data validation and migration - Deploy solutions and implement rollout plans |
| Topic 3: Discovery | 18% | - Evaluate performance metrics and identify improvement areas - Analyze existing business processes and workflows - Define rollout strategy and project scope - Assess technical architecture, data governance and limitations |
| Topic 4: Configure and Build | 38% | - Set up users, permission sets and access controls - Implement Manufacturing Intelligence and analytics - Build integrations and data migration processes - Configure service experience and partner collaboration - Configure core features: Sales Agreements, Forecasting, Rebates |
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92. Frage
Universal Containers (UC) is implementing Advanced Account Forecasting for its national business. UC has three primary product materials it wants to forecast for each of its key distribution partners. Each of UC's individual products has one of these material attributes on its record, but UC doesn't need to see the product detail in its forecast.
What should the administrator do to meet these business requirements?
Antwort: B
Begründung:
To meet the business requirements of UC, the administrator should add a custom Material dimension to the Forecast Fact and Forecast Set objects. This will allow UC to group and filter the forecast data by the material attribute of the products. The administrator should also clone and use the standard DPE definitions to populate the new custom metrics for the Material dimension. The standard DPE definitions are templates that can be used to aggregate data from various sources, such as sales agreements, orders, opportunities, and custom objects. By cloning and using the standard DPE definitions, the administrator can save time and effort in creating the formulas and filters for the new custom metrics. The administrator does not need to configure a custom Forecast Context or create new DPE definitions from scratch, as these options are more complex and require more customization. References: Create Holistic Forecasts with Advanced Account Forecasting, Set Up Dimensions and Period Groups, Streamline Forecast Calculations with Data Processing Engine Definitions
93. Frage
Which two key performance indicators can be calculated on the Forecast Analysis dashboard in Tableau CRM for Manufacturing?
Antwort: D,E
Begründung:
The Forecast Analysis dashboard in Tableau CRM for Manufacturing is a tool that helps business analysts evaluate the accuracy and quality of the account forecasts generated by the Manufacturing Cloud. It allows them to compare the actual revenue with the forecasted revenue, as well as the planned revenue, for each account, product, and product category. It also shows the mean absolute percentage error (MAPE) in the forecast, which is a measure of how close the forecast is to the actual revenue. The lower the MAPE, the better the forecast. The dashboard also provides other metrics, such as forecast bias, forecast coverage, and forecast attainment, to help analysts identify areas of improvement and optimize the forecasting process1. References: Protect and Grow Your Business Unit, Forecast Analysis Dashboard, How Forecasting Works in Tableau
94. Frage
Universal Containers (UC) currently uses Sales Agreements to track its annual plans with customers but is working with a consultant to set up Advanced Account Forecasting.
UC stores shipped/invoiced order data in a child-custom object related to the standard Order object. UC has two primary requirements:
1) To see its forecast by Product Code and Product Category
2) To see actual order data broken out into three metrics: Quantity Ordered but still Open, Quantity Ordered but Shipped, and Quantity Invoiced How should a consultant set up Advanced Account Forecasting to fulfill these requirements successfully?
Antwort: C
95. Frage
What is the proper utilization of a System Integration Testing (SIT) environment?
Antwort: A
Begründung:
A System Integration Testing (SIT) environment is used as an environment to perform system-to-system testing. This means that the SIT environment is used to test the integration of different systems or components that are part of the Salesforce Manufacturing Cloud solution. The SIT environment allows the verification of the functionality, performance, and reliability of the integrated systems, as well as the identification and resolution of any defects or issues that may arise during the integration process. The SIT environment is typically a replica of the production environment, but with a smaller data set and lower security requirements.
The SIT environment is also used to validate the data migration and synchronization between the source and target systems, as well as the compatibility and interoperability of the APIs and web services that are used for the integration. References:
Manufacturing Cloud - Salesforce
How to Perform Automated Integration Testing in Salesforce
Automate and Test During Integration
96. Frage
A customer is concerned about whether data for accounts, contacts, and products should be managed in Salesforce exclusively.
What should a consultant recommend?
Antwort: A
97. Frage
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