A few months ago, I was talking to my next door neighbor Jeff about what he does for a living. Jeff works at a large private investment bank downtown, and he was tasked with sorting out their organization of data. This particular bank is like a lot of financial institutions in that it has data coming in from various feeds, it has data about its own customers, and it merges and presents this data to various groups within the organization. Each group furthermore has its own uses for the data, and may have come to have its own interpretations of the underlying data due to years of healthy growth. Jeff was asking me if I knew of any good books on the subject of data management that might help him sort through all of the issues that were coming up.
I tried to think of a few titles, and we came inside my house to peruse the bookshelves, but after a few moments of page flipping I had to inform him that I really didn’t know of any good books on the subject that would help him in particular. You see, Jeff already had a good handle on general principles on how to approach the problem (better than most) coming from the management side, and he was quickly picking up the general technical principles and the associated language. And that’s where the problem was: while there were any number of excellent references on general data management from a technical point of view, there were none of which I was aware that would help him further along in his particular situation.