The Perils and Promise of Real-Time Data

As the demand for real-time data increases, as more and more information flows into the enterprise and its systems, the challenge of understanding and managing it grows proportionately. And sometimes, more is just too much.

When you first meet CIO Ron Rose, he's more than happy to tell you about the 70,000 or so things that can go horribly wrong at Priceline.com, the consumer travel company built solely on a website that, in 2006, gets 10 million page views a day and books nearly $3 billion worth of travel transactions annually.

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Generally speaking, those 70,000 data points are monitored on a real-time IT system dashboard. The company has been testing new dashboards that offer up-to-the-second information and correlation analysis on numerous systems, including the state of the plumbing and network operations; CPU utilization; various application metrics (how much time is needed to transfer data within the system); Oracle database performance; BMC-monitored performance of things like I/O utilization; operating system paging (how much data is moving to and from the systems disks; and if the operating system is running out of RAM to work with) and a whole lot more.

All those metrics (and more) are crucial to Priceline.com's business as illustrated by a recent Harris Interactive consumer study that found that 40 percent of online consumers will abandon their transaction (or turn to a competitor) if their initial attempt to interact with a site is foiled.

So Rose and his IT staff collect and analyze a torrent of real-time data to identify, prevent and fix problems before that happens. And he says being able to do so has saved the company millions in downtime and repair costs over the years. "Winning by not losing," he calls it.

Rose's IT group isn't the only beneficiary of Priceline's real-time capabilities. Priceline's business analysts tap into a business activity monitoring (BAM) system, which can slice and dice up-to-the-minute information detailing the types of airline tickets, hotel rooms or car rentals that are selling, the completion percentage of different types of orders and (much) more.

All those data points (and more) give business users the ability to see trending demand for specific airline or hotel offerings, or whether visitors are completing transactions or bailing out at the last minute on certain products. The business users can then adjust that data to generate more sales. "[The business group's] hourly reports, which summarize the financial data as it moves through the company, is the MTV of the technology department," Rose says. "They love to keep their fingers on the pulse."

But with that dependence on such fast-moving and variable data, Rose acknowledges that users also have to be aware of any noise lurking in the system—for example, when there might not be a statistically valid amount of data (say, too small a sample size for one of Priceline's sales categories, such as bookings at one of its smaller hotels), which a business user may think is a trend when, in fact, it's not. "It takes more than just a few minutes to make a trend," he cautions.

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