Whats the difference between a data warehouse and an OLTP system? Well there are a bunch of differences, but David Aldridge has an interesting take on tuning in his new blog He describes a tuning exercise that resulted in execution times that were massively improved. The only problem, the end-users didn’t care.
I think David has nailed part of the problem, the attention-span thing, but I think that part of it comes down to the DSS vs OLTP bias that he has (mine is the exact opposite). Most reports, or batch users, expect their process to take some time, sometimes really a lot of time. This isn’t a problem because you often don’t interact with a report, you analyse it, you think about it, you have meetings about it and then you implement something (or perhaps don’t implement something you were going to do). Now the business might well like this process to take a shorter period of time, but it probably isn’t the running of the report that takes the time, its all the clever application of human intelligence to business data (which sadly we don’t have instrumented yet). In an OLTP environment though you want your data entry people to enter as much data in as short a time as possible,(especially of course if you can use the web to persuade your customers to be data entry people for you) – that way you get a large number of transactions at a low cost. Here the time a technical process takes really is a key component and in this environment small absolute changes can have a really big impact.
btw when did we stop doing DSS and start doing Data Warehouses, I much prefer the first name as it suggests the human intelligence bit more than the stockpiling vast quantities of data at high cost for no discernible benefit that the second name suggests.