What your coworker did might be better described as "intelligent parsing" of a string. That could be done at many levels of sophistication -- for example, using statistical models to give you the likelihood that "Dr." is a salutation and not a first name. Or it could just use a simple lookup list of common salutations, in which case it's just regular procedural code, nothing more.
SSIS is short for SQL Server Integration Services. It's basically DTS on steroids; some people love it, and some people hate it. It'd be tricky to use that by itself to do the kind of thing you're talking about; it's mainly just for taking data from various sources and combining it, transforming it, and loading it somewhere else. It can do some nifty things, many of which tend to be data-mining like, but ultimately it's a production tool for cramming data one direction or another. It isn't particularly well respected in the data mining community.
Data Mining is an entire academic discipline, focused on using some (typically large) quantity of data to either predict future answers or better understand patterns in existing data. It's definitely a great area to get into, but not something you can just pick up and do without some intensive study of math and algorithms. A good book on the subject is this one.
"Business Intelligence" is really more of a buzzword than a specific technology, and can mean different things to different people. At base, the idea suggests doing less dumb stuff with business data, and generally it refers to analysis of trends over time, often using OLAP. It may also include data mining or AI algorithms, but since there's no rigorous definition, just about anybody who wants to sell you something will tell you it offers "Business Intelligence", and hope you don't dig any further.