I published an article describing how to implement the grouping of sales transactions by age of customer at the moment of the transaction by using PowerPivot or Analysis Services. The same pattern can be used also for any kind of banding operation, this specific case is useful also to recycle the formula that gets the exact age of the customer for each transaction.
An interesting point is related to performance optimization. The technique is based on adding a calculated column in a table that might contain millions of transactions. This is less expensive than adding a column that contains a foreign key and then a relationship between a table containing group definitions and the transactions table. Every relationship is expensive and generates additional structures (you can see more files in the Analysis Services database, too). Adding one or two columns that have a low number of distinct values (10-15 rows) usually has a lower memory cost than creating a relationship with another table. The article also contains PowerPivot examples for both Excel 2010 and Excel 2013.
If only I could decouple attribute visualization from physical structure, I would put these “degenerate dimensions” in a separate folder, because in this way such attribute will be included in attributes belonging to the fact table, which might not be so clear in presenting data. However, I understand that such a decoupling could make live very hard to DAX clients (but probably for MDX it could be not a big issue).