What is the first step the data architect should take to build this data model to accurately reflect performance?

The data architect has been tasked with building a sales reporting application.

• Part way through the year, the company realigned the sales territories

• Sales reps need to track both their overall performance, and their performance in their current territory

• Regional managers need to track performance for their region based on the date of the sale transaction

• There is a data table from HR that contains the Sales Rep ID, the manager, the region, and the start and end dates for that assignment

• Sales transactions have the salesperson in them, but not the manager or region.

What is the first step the data architect should take to build this data model to accurately reflect performance?
A . Implement an "as of calendar against the sales table and use ApplyMap to fill in the needed management data
B . Create a link table with a compound key of Sales Rep / Transaction Date to find the correct manager and region
C . Use the IntervalMatch function with the transaction date and the HR table to generate point in time data
D . Build a star schema around the sales table, and use the Hierarchy function to join the HR data to the model

View Answer

Answer: C

Explanation:

In the provided scenario, the sales territories were realigned during the year, and it is necessary to track performance based on the date of the sale and the salesperson’s assignment during that period. The IntervalMatch function is the best approach to create a time-based relationship between the sales transactions and the sales territory assignments.

IntervalMatch: This function is used to match discrete values (e.g., transaction dates) with intervals (e.g., start and end dates for sales territory assignments). By matching the transaction dates with the

intervals in the HR table, you can accurately determine which territory and manager were in effect at the time of each sale.

Using IntervalMatch, you can generate point-in-time data that accurately reflects the dynamic nature of sales territory assignments, allowing both sales reps and regional managers to track performance over time.