Page 4 of 4
Complex event processing

Cunningham is CEO of Coral8, which offers complex event processing (CEP), where "you have a continuous pulse line that's monitoring everything in real time."

CEP is an event-processing concept in which multiple events in an event cloud are processed to find the meaningful events. It lets enterprises extend BI down to previously ignored areas such as the shop floor, where "there's a high noise to signal ratio, meaning only a relatively few of the millions of data events are meaningful," Cunningham said.

"The typical database can handle 6,000 inserts a second; we're talking 200,000 to 300,000 events a second in CEP; more than 100,000 is typical," Cunningham said.

CEP analyzes data in real time, and is complementary to existing data infrastructure. "We feed databases, we don't replace them," Cunningham explained.

One of Coral8's customers is Sallie Mae, the nation's leading provider of student loans, which "has this huge command center looking at its Web site traffic in real time," Cunningham said. This is in addition to Sallie Mae's existing BI systems.

Up until now, all approaches to BI, whether traditional or not, have relied on data cleansing -- ensuring that data is consistent and accurate. But data cleansing is a laborious process, and Stef Damianakis, CEO of Netrics, believes it is unnecessary.

"The standard is, first you do cleansing, then you do matching, and then you have this huge effort of getting the data perfect, which is not an achievable goal in practice," Damianakis told InternetNews.com.

LATEST NEWS

Blair Levin Calls for Citizen Participation
Bing Brings Twitter Into the Mix
CSC Teams With Microsoft on Cloud Services
FCC Gets to Work on Mapping Out Broadband Plan
Linux Vendors Head to the Cloud in Search of Cash

"Even if you get your data perfect today, what's going to happen to it over the next week, two weeks, two months? And can you be sure it was entered perfectly into the system?"

Netrics' approach is to use mathematical modeling to get results in spite of imperfect data so that, "instead of focusing on the data standardization and data perfection phases, you can use the data as it is and the model can overcome discrepancies in the data."

Standard methods of querying data with BI tools are clunky because "there is a translation from the question being asked to a set of rules either the business analyst or IT has to write to query the data," Damianakis said.

He suggests that giving the business user the ability to build a mathematical model, or widget, that answers his questions, would be more productive.

Netrics has two products, The Matching Engine, which models human similarity, and The Decision Engine, which mathematically models human decisions. The two can work together or independently.

The company's solutions can "mathematically model human questions," and its technology is embedded in solutions from vendors. Partners include Northrop Grumman (NYSE: NOC), Lockheed Martin (NYSE: LMT) and health care IT system provider Cerner (NASDAQ: CERN).

"Data can never and will never be perfect, and it's time for software to stop requiring that and to build systems that will work even if the data's not perfect," Damianakis said.

Go to page: Prev  1  2  3  4