CI is not necessarily a replacement for a data warehouse. Some CI applications may still require that the data be put in context, and that happens when it is merged with the information from a data warehouse.
"If you calculate the volume weighted average price of a stock at $26.50, you won't know if that is good or bad unless you look up the history," Cunningham says.
Then, of course, there's the clicks: anything that happens online.
Automating ticket pricing by watching airline ticket sales, destinations, and plane capacity has been around for quite awhile, and it has helped push the market for CI into the broader context of all e-commerce.
Continuous intelligence: Old concept, new possibilities
The concept isn't new even in retailing. The change now is that the concept can be actualized.
Way back, Compaq coined the phrase "ZLE," for "zero latency enterprise." The classic ZLE example was of a shopper using a store credit card at checkout and while the product was being scanned, the technology would match the purchase -- in nanoseconds -- with past customer purchases, current store-inventory levels, margin, sales forecast for the item, and likelihood to buy again. It would take the results of all that and make a new offer before the receipt would be printed out.
A simpler example is when CI monitors customer behavior and uncovers that the potential buyer has come back three times to check the price. On the fourth time, they are hit with a special offer.
Sallie Mae uses Coral8 to track online loan applicants in order to better understand abandonment rates, improve performance, and do what those brick-and-mortar retailers do: make a personalized offer.
But while the idea was very attractive in the mid-'90s, the technology is only now catching up. Multicore processors and huge amounts of cache memory are enabling practical applications of this new kind of database to store information in memory, analyze it, and then dump the data or push it off to the standard database when done.