The two most popular methodologies for building a data warehouse (DW) seem to be Bill Inmon's and Ralph Kimball's.
Inmon's methodology uses normalized approach, while Kimball's uses dimensional modelling -- de-normalized star schema.
Both are well documented down to small details and both have many successful implementations. Both present a "wide, well-paved road" to a DW destination.
I can not comment on the 6NF approach nor on Anchor Modelling because I have never seen nor participated in a DW project using that methodology. When it comes to implementations, I like to travel down well tested paths -- but, that's just me.
So, to summarize, should DW be normalized or de-normalized? Depends on the methodology you pick -- simply pick one and stick to it, at least till the end of the project.
EDIT - An Example
At the place I currently work for, we had a legacy report which has been running since ever on the production server. Not a plain report, but a collection of 30 sub-reports emailed to everybody and his ant every day.
Recently, we implemented a DW. With two report servers and bunch of reports in place, I was hoping that we can forget about the legacy thing. But not, legacy is legacy, we always had it, so we want it, need it, can't live without it, etc.
The thing is that the mess-up of a python script and SQL took eight hours (yes, e-i-g-h-t hours) to run every single day. Needless to say, the database and the application were built over years by few batches of developers -- so, not exactly your 5NF.
It was time to re-create the legacy thing from the DW. Ok, to keep it short it's done and it takes 3 minutes (t-h-r-e-e minutes) to produce it, six seconds per sub-report. And I was in the hurry to deliver, so was not even optimizing all the queries. This is factor of 8 * 60 / 3 = 160 times faster -- not to mention benefits of removing an eight hour job from a production server. I think I can still shave of a minute or so, but right now no one cares.
As a point of interest, I have used Kimball's method (dimensional modelling) for the DW and everything used in this story is open-source.
This is what all this (data-warehouse) is supposed to be about, I think. Does it even matter which methodology (normalized or de-normalized) was used?
EDIT 2
As a point of interest, Bill Inmon has a nicely written paper on his website -- A Tale of Two Architectures.
