Yes, this indeed is an excellent, detailed overview look at data warehousing.
However, as others have suggested here, the data warehousing concept would not exist except for its value to the business and management. In that regard, it is imperative to remember that the central reason for DW at all is to provide pre-calculated and massaged data to management and the business. In this manner, all calculations for a particular count or equation can be managed and, hopefully, the entire enterprise will be looking at the same number calculated in the same way at a given time.
As indicated in your diagram, there are usually two distinct types of data that can be reported on and which require entirely different processing methods. OLAP (cubes) can do an excellent job of calculating based on historical records kept in a cube structure but is not as efficient at state data. State data is not usually historical and benefits from the data warehouse's ability to summarize data across the enterprise, joining data from probably very disparate systems.
Also, it is important for the enterprise to pay close attention to data warehouse metadata as depicted in your very accurate diagram. Metadata is the prime tool in the data warehouse for managing data quality. In this manner, all incorrect and inappropriate data can be automatically categorized and attended to by the data quality team through use of metadata reporting functions. Another aspect of this feature is the transparency of data quality. With proper data quality reporting, it should be patently obvious which data source is providing good data and which is not.