Back in 2004, we were decided to denormalize a set of records containing year, quarter, and 15 or so data points going back to 1996. Using this cross-tab method, we started out with 8 (years) * 4 (quarters/year) * 15 (data points) = 480 columns (a few more for non-denormalized data). 5 years later, we're up to the high 700s. Needless to say, this pretty much blows out your standard MySQL admin tools.
Another pitfall is, you really have to make sure you data is pristine (of course you should be doing that anyway, but reality is usually far from ideal, especially if you're me in 2004), otherwise you end up with doubling of values or values included when they shouldn't be. The generated queries are very very difficult to debug, again blowing out many admin tools and also text editors (unless you add pretty formatting in your query generator).
So what would I recommend instead? There are multi-dimensional databases or ETL tools that will properly put your transactional data in an analytical style data warehouse. Read Kimball's Data Warehouse Toolkit [1] (ignore the kinda ratty paper quality—the content is good). The key thing is to denormalize down to a star schema, but keep your facts and dimensions separate (things you'll learn in DWT).
There's an Java based OLAP server called Mondrian [2] that also may be worth your time. I ended up going with ActiveWarehouse and ActiveWarehouse-ETL [3], but I've felt some things a little more complicated than they needed to be (but that's another discussion—and I haven't kept up with their development lately, so it may have improved).
On a side note, recently I've started wondering if map-reduce style tools would make sense in this context, but I haven't explored using them that way yet, so I can't actually make a recommendation there.
[1] http://www.amazon.com/Data-Warehouse-Toolkit-Complete-Dimens...