If you need to aggregate data and make it available to slice and dice it at the speed of thought, you should use SSAS. There is no comparison, in this regard, between a multidimensional database (aka a cube, or what SSAS builds) and a relational one.
You can attach a lot of things to SSAS. Microsoft's product is PerformancePoint and ProClarity, but Excel comes with a native connector. If you have SharePoint, it can natively attach to KPI's from SSAS. You can also use SSRS to present the data. With a cube, you'll be amazed at how much more you can do than just look at a few metrics. It's truly awesome and powerful stuff. Also with a cube, you can more easily use Data Mining and the like.
I have to say, though, that you'll at least need to build a mart in a star schema to build the cube off of. There are plenty of fantastic books about this, but I'd recommend the Data Warehouse Lifecycle Toolkit by Ralph Kimball. It gives a great overview of what marts can do, and why you'd use them. For picking up SSAS, there's Analysis Services Step by Step, which guides you through the process of building up a cube.
After spouting on about how awesome cubes are, I have to give this disclaimer: If all you want to know are a few metrics from a small dataset, don't worry about a cube. T-SQL is better (by the way, SSRS works arguably better with T-SQL than with SSAS). If you really want to be able to explore the data and jump across all sorts of aggregated levels quickly, then you want a cube. After that, the presentation layer is what you feel most comfortable with. T-SQL and SSAS are compatible with the same MS products.