After the Web 2.0, it's time of BI 2.0. Everyone of BI area agrees that a lot of changes are happening, although several important analysts and professionals of industry try to resist the use of the name Business Intelligence 2.0.
Although Business Intelligence 2.0 is a buzzword, with a convenient marketing of the version number, the concepts proposed are quite interesting. By the way, there is nothing new about most of the concepts, what is changing is how to integrate with BI, through new approaches. The BI 2.0 is an extension of the traditional BI, not replacing it only complementing. Some concepts of new BI are based on the concepts of Web 2.0.
The BI 2.0 includes the concepts and technologies of data mining, statistical analysis, advanced visualization, mobile technology, alert notifications, rich reports, predictive analytics, BI search, text analytics and semantic data model.
The BI 2.0 also takes advantage with the concepts, processes, architectures and technologies that improve business process and event processing, as Service-Oriented Architecture(SOA), Business Process Management(BPM), Business Activity Monitoring (BAM), Complex Event Processing(CEP) and Event Stream Processing(ESP).
While the main function of traditional BI (sometimes called BI 1.0) is to analyze the past, the BI 2.0 is to predict the future, using the concepts of traditional BI together the concepts of BI 2.0 to build a smart picture. The BI 2.0 is more pro-active than reactive. The traditional BI is closed loop, unable outside input data, because it occurs after the events, and BI 2.0 is open loop because enable input data when the events occur, and its real time analysis.
The BI 2.0 is more intuitive, interactive, pervasive, collaborative and process-driven.
The main effects of BI 2.0 in the companies are: Data integration and comprehension (using Master Data Management), roles (people with many roles at the same time), lower cost of BI licensing (many people using BI), convergence of structured and unstructured data, convergence with the rest of operations.
But one of the most important concepts of BI 2.0 is not about technology, is about people. The technical innovation is the easy part, the hard is to align the organization. It is important to focus on people, remember that with the continuous technical innovation, people are taking cultural shifts, and people will use insights, a new way of thinking and the concepts of social networking and collaboration to work more effectively.
The BI 2.0 allows a BI for everyone, not only for executives, power users or information workers, and extends beyond corporate boundaries, to suppliers and customers.
The traditional BI makes the deal, is useful and keeps alive, but BI 2.0 will provide a new way for the companies improve their results.
Showing posts with label Real-Time Enterprise. Show all posts
Showing posts with label Real-Time Enterprise. Show all posts
Sunday, April 27, 2008
Monday, March 10, 2008
The Real-Time Enterprise and the Right-Time Business Intelligence
In the beginning of Business Intelligence, a several years ago, when the BI projects were defined only to use in the strategy level, the data warehouse was normally updated monthly, and sometimes weekly, in some specific areas.
Nowadays, the companies need to make decisions quickly, and with the expansion of BI for operational applications, update the data warehouse has become increasingly in near real time.
We are in the era of real-time enterprise, and the data need to be updated according to the business requirements, in some cases, less than a second after after a business event has happened in a transactional system.
The process to get information almost without latency in the business event is called Real-Time Business Intelligence and the process to delivery information when it is required is called Right-time Business Intelligence. The difference is Right-Time BI can not be necessarily in real time.
Although the latency depends of the kind of business, and all BI systems have some latency, it is important define which time is better to update the Data Warehouse, that can be less than a second, seconds, minutes, hours or daily, according to serve the business requirements. For define this time, you should know that as more you reduce the time of data latency, you will reduce the time to take action.
Some areas where is very interesting to apply the concepts of Real-Time BI are: financial markets (stock exchange), fraud detection, application performance monitoring and risk management.
Some kinds of application don't need of real-time BI, because don't need to update the data warehouse frequently. There are cases where if you implement the Real-Time BI, this will be a hindrance, because the data updated quickly can affect the analysis. For example, a sales application where the customers normally emit orders once a week, if you update the data warehouse daily, and try to analyze the results in 3 or 4 days, you can make wrong decisions, because sometimes several orders are emitted in the last days of the week.
I think the concept of Right-Time BI is comprehensive and interesting, you delivery information when it is required, being real time or not.
P.S. - The term Right-Time Business Intelligence was coined by Colin White, in a report of The Data Warehousing Institute (TDWI), entitled “Building the Real-Time Enterprise”.
Nowadays, the companies need to make decisions quickly, and with the expansion of BI for operational applications, update the data warehouse has become increasingly in near real time.
We are in the era of real-time enterprise, and the data need to be updated according to the business requirements, in some cases, less than a second after after a business event has happened in a transactional system.
The process to get information almost without latency in the business event is called Real-Time Business Intelligence and the process to delivery information when it is required is called Right-time Business Intelligence. The difference is Right-Time BI can not be necessarily in real time.
Although the latency depends of the kind of business, and all BI systems have some latency, it is important define which time is better to update the Data Warehouse, that can be less than a second, seconds, minutes, hours or daily, according to serve the business requirements. For define this time, you should know that as more you reduce the time of data latency, you will reduce the time to take action.
Some areas where is very interesting to apply the concepts of Real-Time BI are: financial markets (stock exchange), fraud detection, application performance monitoring and risk management.
Some kinds of application don't need of real-time BI, because don't need to update the data warehouse frequently. There are cases where if you implement the Real-Time BI, this will be a hindrance, because the data updated quickly can affect the analysis. For example, a sales application where the customers normally emit orders once a week, if you update the data warehouse daily, and try to analyze the results in 3 or 4 days, you can make wrong decisions, because sometimes several orders are emitted in the last days of the week.
I think the concept of Right-Time BI is comprehensive and interesting, you delivery information when it is required, being real time or not.
P.S. - The term Right-Time Business Intelligence was coined by Colin White, in a report of The Data Warehousing Institute (TDWI), entitled “Building the Real-Time Enterprise”.
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