Business intelligence defines an array of applications that gather, store, analyse and access data to help business decision-makers. Basically it looks to historical data in order to create information and reports that drive the future of the business.
The obvious problem is that the data is not current, which detracts from the value of the information supplied to decision-makers. How old that information is depends on resources allocated to it and the importance of the project driving the business analysis. BI draws on the business`s back-end data repositories to deliver snapshots of the business or create historical analyses.
Wikipedia states that the challenge in business is to:
* Collect data;
* Discern patterns and meaning in the data (generate information); and
* Respond to the resultant information.
The problem with historical data is that it`s after the fact. The news is old, the coffee cold. And it`s no use locking the stable door after the horse has bolted. Stream-oriented analysis, on the other hand, catches the data as it is created and analyses it as it flows toward the data repository. It distils the information that systems automatically collect and generate to stem the rising tide of information fatigue sweeping business people around the globe.
Hooked into front-end systems, it can be defined as activity-based monitoring that, for example, gives the organisation insight into the trends or preferences of surfers to its Web site. This is done by trapping transactional activity as surfers interface with the Web site, in real-time, as extracted from Web site log files and cookies.
Process-related data
It is process-related data that is trapped, not data related to business items such as client details or product information. For example, if a consumer opens a form on a Web site, then the fact that a consumer wants to place an order is extracted. That the consumer clicked on a specific link directed at a specific location containing a specific form is immaterial to the business person. The business only wants to know that a consumer wants to place an order, or that consumers read about the products but never place orders. That`s information they can use.
Stream-oriented analysis catches the data as it is created and analyses it as it flows toward the data repository.
Mervyn Mooi, director at Knowledge Integration Dynamics.
It`s invaluable to businesses as they attempt to ascertain user, customer and Web site visitor preferences. Armed with that knowledge, they can tailor the user`s experience to improve it and ultimately sell more product or service or even revolutionise the business.
AOL has embarked on a stream-oriented analysis project. AOL is also restructuring. Some pundits reckon the business is shying away from its Internet access and media content past toward a product- and service-oriented future. Apparently, subscribers only used its access services and barely touched the content.
Stream-oriented analysis is the perfect companion to a company in AOL`s position.
A company like AOL can analyse each and every surfer`s session on its Web site if needed. Or it can assess a specific step in a process as it affects multiple users. This is not an hour after the session, or a day, a week, one or even several months later. The analysis is presented seconds after the event and is close enough to real-time to almost be the real thing.
AOL has millions of subscribers. At any one time it has over three million members online. That is a powerful volume of data stream it can filter, analyse, gather and store. It gives the organisation invaluable information into the preferences of the market it serves.
Stream-oriented analysis is also saleable and marketable.
Data has always been classified as a non-revenue-generating asset. But the statistics deduced from a stream-oriented analysis collation can be sold. This doesn`t infringe on privacy rights or laws because it is not about specifically identified people. The more current the information the more valuable it is.
Stream-oriented analysis is going to have a fundamental impact on the world of business intelligence.
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