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• Scalability: Using Calculated Dimensions allows the client to apply the same harmonization logic to future data streams, ensuring consistency and reducing the need for individual adjustments.
• Ease of Maintenance: With the logic centralized in Calculated Dimensions, any adjustments or updates are applied in one place, simplifying ongoing management.
• Performance: Calculated Dimensions can improve dashboard performance because their values are pre-computed and stored, reducing the need for real-time calculations when loading dashboards.

Option 4 presents two calculated measurements for 'Group Min Cost' with 'MIN' and 'AVG' aggregations. This approach aligns with the client's need for the minimum and average media cost values. 'Group Min Cost 4 MIN' will calculate the minimum media cost across the 'Media Buy Key', while 'Group Min Cost 4 FINAL' will average these minimum costs at the 'CampaignKey' level. This will yield the desired result where minimum costs are calculated at the Media Buy Key level and then averaged at the Campaign Key level.

If the harmonization logic consistently associates a single Exam Topic with each Exam ID across all data sources, then creating two harmonized dimensions may be unnecessary. One harmonized dimension for Exam Topic would suffice because it inherently carries the Exam ID's uniqueness within it. The harmonized dimension for Exam Topic would allow the client to slice the data by Exam Topic values, fulfilling the requirement.

Based on the Opportunity file and considering the filter dates from January 7th to 10th, the different stages presented are 'Interest', 'Confirmed Interest', and 'Registered'. This makes a total of 3 different stages that would be presented in the pivot table. Salesforce Marketing CloudIntelligence allows for the creation of pivot tables that can display counts of entities across different dimensions, in this case, Opportunity Stages. Reference to Salesforce Marketing Cloud Intelligence documentation that covers data mapping and pivot table creation would support this conclusion.

In Marketing Cloud Intelligence, attributes refer to characteristics of the data that describe the environment or context but do not change within the scope of the data being analyzed. 'Device Category' is typically an attribute as it describes a characteristic of the device used and doesn't vary within a given session or user interaction. In contrast, variables are typically metrics or dimensions that can change value or be measured.