Business intelligence, in the traditional sense of the term, is undoubtedly a powerful strategic tool, which helps enterprise users to transform data into information, information into knowledge and knowledge into actionable strategies and tactics. Traditional BI systems have helped to improve the strategic decisions that affect the success of a business. This, however, is not enough in today's dynamic growth of the business and it also has little tactical value that reacts to immediate events. A solution enabling this type of capability is known as Real-Time BI (RTBI).
Real-time BI is also known as event-driven BI. In order to react in real-time, a BI system must react to events as they occur – not minutes or hours later. With Real-time BI, an enterprise can establish long-term strategies to optimize its operations and maximize competitiveness while at the same time reacting with the intelligence to events as they occur.
The gap between analytical (in the traditional sense of the term) and operational (Real-Time) processing is fast. The complex event processing tools and data-mining queries that used to take hours to run now execute in seconds. If only these data-mining engines had the latest values of the data, the tactical and strategic needs of BI could be merged into a single solution. However, In order to succeed, businesses should overcome two primary challenges: data latency and data unavailability.A business cannot respond to events as they happen if it cannot find out about these events for hours, days, or weeks (data latency). It also cannot immediately respond to events if the system that supplies the analyses of these events is down (data availability).
Real-Time BI represents a significant improvement in reducing data latency and enabling actions to be taken within hours of the events that triggered them; however, they do not meet the criterion of immediacy that will allow a business to react in real-time to an event. Such triggers can post changes captured in the source system into a separate staging area, and the real-time integration engine can read continuously from the staging area without affecting the performance of the source systems. The cost and complexity involved in implementing specialized tools only to replicate data may not justify the benefits received by providing the information earlier.
The growth dynamics of the business, the available time limits for decision-making are increasingly shorter, both at the operational and at the strategic decision-making level. This leads to changes in the principles of the decision making, which is reflected in the requirement that the operational and strategic decision-making share the same platform and the same tools of BI, which was almost unthinkable until a couple of years ago. With real-time changes reflected into BI solutions, a whole new platform is open to the users where they can access up-to-the-minute operational information. This is superior to traditional BI solutions where users have to wait for a day or more to get the same information as the source application contained.
Despite of the understood value of Real-time BI, not every situation requires this approach, says Graham Mackintosh, business unit executive for IBM Cognos. “Real-time BI only makes sense in situations where you can respond to its findings in real time. Extremely low latency is only helpful if there is measurable business benefit and return on investment to be gained from quick responses.”
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