Of the most common techniques for optimizing performance of a Data Warehouse are: __check all that apply ___

		For a very large database, implemented in a dispersed geographical area, a table can be partitioned into subsets of row, or columns, according to location of the client computer..
		Denormalizating the structures can improve performance by storing in a single record a set of columns that normally would be designed to be stored on many rows on different tables.
		When designed, a data warehouse may hold a granular level of detail for historical data. Queries derive levels of aggregation by summarizing lots of detail for generating graphics. For frequently run queries it speeds up the execution if levels of aggregation are computed at data loading time rather than at run time.
		By normalizing the design of dimension tables, data filtering operations related to the dimensions are simplified. This helps to facilitate navigation through schema by the end users.