The SAP BW live model is a type of live data connection that allows you to access data from SAP Business Warehouse (BW) systems without importing it into SAP Analytics Cloud. The SAP BW live model supports the following calculation types:

• Aggregation: You can use aggregation functions, such as SUM, COUNT, MIN, MAX, etc., to calculate the values of a measure based on a dimension or a filter.
• Currency conversion: You can use currency conversion to convert the values of a measure from one currency to another based on predefined exchange rates.
• Unit conversion: You can use unit conversion to convert the values of a measure from one unit of measurement to another based on predefined conversion factors.

The SAP BW live model does not support the following calculation types:

• Dimension to measure: You cannot convert a dimension to a measure in a SAP BW live model.
• Date difference: You cannot calculate the difference between two dates in a SAP BW live model.
• Story calculation: You cannot create story calculations in a SAP BW live model.

Therefore, the correct answer is Aggregation, as it is the calculation type that the SAP BW live model supports. Verified References:

• : Create Calculations in Models
• : SAP BW Live Data Connection

The model setting Optimize Story Building Performance prevents the automatic refresh of data during story design. This means that users can design stories without waiting for the data to load every time they make a change. Users can manually refresh the data when they want to see the updated results. The model setting does not affect the design experience, the parallel processing, or the story editing. Verified References: [SAP Analytics Cloud - Optimize Story Building Performance]

The link type determines how the data from the primary and secondary models are blended in a story. There are three link types: Primary, All, and Intersection1.

• Primary: Only the data from the primary model that matches the data from the secondary model is displayed. This is equivalent to an inner join in SQL.
• All: All the data from both models is displayed, regardless of whether they match or not. This is equivalent to a full outer join in SQL.
• Intersection: Only the data that exists in both models is displayed. This is equivalent to an intersection in set theory.

In this case, the link type that returns what data is Intersection, because it only shows the data that is common to both models, such as Customer A and Customer B. Customer C and Customer D are excluded because they do not exist in both models.