When dealing with dimensional modeling challenges, particularly the one-to-many joins problem in SQL queries, it's crucial to avoid duplicating aggregated values, as illustrated by the example of calculating total costs and quantities from orders and order items. A naive SQL query can inadvertently count order totals multiple times due to one-to-many relationships, leading to inaccurate results, such as inflating the total cost for states like Alaska. Looker addresses this with a patented technique called symmetric aggregates, which involves complex SQL to ensure each order contributes to the sum only once. However, this method has drawbacks, including complexity, potential performance issues, and the use of slower distinct aggregates. An alternative approach is to apply multiple levels of aggregation through subqueries, transforming the one-to-many relationship into a one-to-one, which simplifies the SQL and avoids expensive distinct operations while maintaining accuracy. Although subqueries can be inefficient in older systems, modern data warehouses handle them efficiently, making this a viable strategy for manually written SQL queries, despite not being commonly used by BI tools.