http://en.wikipedia.org/wiki/Dimensional_modeling http://www.amazon.com/Data-Warehouse-Toolkit-Complete-Dimens...
Redshift is indeed a solid product but all these comparisons against Hive are surprising, as that's not the right tool in the first place. Infobright, greenplum, aster, vertica, etc are the products which Redshift seeks to disrupt.
At my university, standard normalisation was taught in the "databases" course. OLAP was mentioned as part of the "advanced databases" course.
The database course at that time blew about half its time on building PHP applications to talk to the database. I hate to second guess my professors, but I can't help but feel that a more productive use of the time would have been to teach normalised OLTP in the first half, and dimensionally modelled OLAP in the second half. Better yet, to divide them into two courses and spend some time talking about database history ("here's why network and hierarchical databases sucked") and maybe some introduction to how query planners work.
It's a bit old, but still pretty good.
Edit: actually, maybe not Date. It's up to you. It's good, but it's controversial because he's not a fan of SQL and so he uses his own language.
The one I used in uni was Ramakrishnan & Gehrke's Database Management. It was OK but there's a certain amount of at-the-time trendy bullshit that to me detracts from a focus on relational databases for their own sake.
Edit 2: and Joe Celko's SQL for Smarties contains good oil on the relational paradigm.
One thing to be aware about with both is the lack of any support for wide tables - Infobright inherits MySQL's limit of 65,535 bytes per row (and UTF8 means 3 bytes per char); with Redshift you can stored wider rows but you can't query them (http://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_TABLE...). Obviously not a deal breaker, but it locks you firmly in the densely populated rows, relational mindset.
This aside, we're super-excited about Redshift!
Btw, do you have more experience to share? e.g. with infobright, how many events can be processed per second? what would be the "ETL latency"? can infobright handle 10TB of data easily, any caveat besides the row limit? Thanks.
And even for moderate data sizes (10+ GB per table), row store DBs tend to become painful. This is especially true when you need to support ad-hoc reporting queries, since the usual technique of matching your schema, indexes, and queries won't be effective any more. With true ad-hoc reporting, your only hope becomes lots of shallow indices rather than ones tuned to a particular query.