I have a few problems with one of my topic choices at uni this semester. It's not that it's a particularly bad topic or, worse, inconveniently scheduled. I think I can best illustrate my problem with a bit of background information followed by some quotes from the first lecture.
Data Mining and Knowledge Discovery is a third year database topic offered in odd years only. It is taught by Roddick, who may be remembered as the DB1 lecturer from last year. Whilst learning about Databases from him I felt that, although he at first appeared to be a nice guy he was, in fact, actually a real life version of Bowser, the evil overlord of the Mario universe. But he taught databases and they are important so I learnt from him and eventually jumped over him and landed on the hammer behind him to pass DB1.
So what is Data Mining? Roddick explained it like this. Initially there was Data Queries, where you had a question to ask and a general idea of what answer you would find. Then came Data Analysis, where you knew what your question was but had no way of determining what the answer could be. Then there is Data Mining, in which you don't have a question and you don't know what the answer will be like.
I'm sorry, but that's not "Data Mining", Roddick, that is "You making up random shit about databases". If you don't have a question or an answer you're not "mining", you're "not doing anything". Of course, not doing anything is much easier to get paid 30 grand a semester for compared to mining.
Roddick was particularly proud of his efforts in establishing this fraud so sturdily. He talked about how if anyone thought of Data Mining, they thought of Flinders. He then compared this to how if anyone wanted Biochemistry they thought of Adelaide University. The only real difference being that Biochemistry is non-fictional.
I like Roddick; I enjoy the way in which he surrounds himself with an air of authority as a Data Mining expert. He seemss like the Dungeon Master in Dungeons and Dragons. He creates an intricate reality in which everything he says seems crucial and important when, in actuality, he is just a big nerd making up random crap.
He finished the lecture by informing us that there was "large scope" to undertake Honours as a Data Mining PHD student. Seems there's not much demand to specialise in such a cutting edge field. I wonder why.