Defining Business Intelligence
As academics, we are often working with concepts and ideas, and when we are researching these concepts, we need to have explicit definitions that specify what is, and what isn't, of interest to the study. Sometimes, as with the case of Business Intelligence, there is a fairly strong, but implicit, definition used in industry, which is fine, since an explicit definition beyond a specific project doesn't really matter too much.
However, for academics, this can create difficulties. Without an accepted explicit definition, particularly for a hot-topic like BI, academics jump on the bandwagon claiming the area as part of their expertise without justification. Recently we've been working with some academics from the harder end of the IT spectrum, and we've struggled to make the point that the 'intelligence' bit of BI is not the same as the 'intelligence' bit of AI, or even human intelligence, but rather in the sense that Herbert Simon used it: ie. monitoring and gathering information to support decision-making.
But even that doesn't really solve much. Some people view BI as just the hardware and software tools that support that process. Others see the process itself as BI: Ralph Kimball, for example, famously uses a publishing metaphor in relation to data warehousing. Some see BI as the delivery layer or front-end, and treat data warehouses as something quite separate. Others would include the whole information supply-chain as BI.
So, what is BI to you? Is it any technology that supports organisational decision making? Is it specifically reporting and analytics? Does this include enterprise reporting, or does BI go beyond a kind of passive, push technology? Does BI extend beyond supporting decision-making to the actions that result from a decision? What about operational versus strategic decisions?
Leave a comment and let us know.
6 comments:
For the scope of BI, in my opinion it extends from the back-end (data warehouse) to the front-end (OLAP, reports) layers. Subsequent actions and decisions are beyond BI, as they are independently undertaken by the users that a BI system supports.
I would argue that all these systems are what Business Intelligence needs to deliver information for managers or whoever else that needs them. To develop a proper BI system to any company, you would need a sufficient data warehouse to provide suitable data, as traditional relational databases are slow and may not have the appropriate structure for BI. On the other hand, data warehouse alone isn't enough to be able to present data to business users, as they need the simplicity of reports or the flexibility of analytical tools such as OLAP.
Having said that, with regards to the technology, today's world is inevitably linked with the role of computers and technology. Thus, Business Intelligence is best delivered using technology. It's probably the same information delivered in the past by personal assistants, secretaries, intelligence officers, and the like.
But today, computers outperform them all in terms of speed, efficiency, and accuracy. Of course, they can't do much when it gets to opinion, judgment, and complex political decisions. However, my point is that the technology aspect is just one that comes with the advance of modern age, but, by pen and paper, the essence of BI has been here for a long time.
I believe BI is not the technology. I also believe that 'subsequent actions and decisions' are within the scope of BI. They are part of the BI cycle / process used to gather and analyse data for the purpose of providing useful information (the intelligence) in decision making. The cycle can be seen in the following example. An organisation sets some goals. Using data they analyse their progress on achieving these goals. This may or may not be done using BI related technology, but BI presentation tools certainly support these analysis efforts and allow the results to easily be shared amongst others (prompting possible feedback). The analysis can lead to insight. Insights may end up as actions. Over time, these actions can be measured to ensure they were the correct ones or are still working. This may lead to more data for further analysis and further action, where the cycle can begin again.
I tend to agree, Andy. This certainly matches with the idea that BI tools are evolutionary (ie. they never finish being developed and modified). Even strategic, once-off decisions should have some measurable outcome, although that raises the problem of tangible and intangible benefits - something Marcus talks about over at 401percent.
Late to this party, but still, here's my opinion, for what it's worth...
As reporting and on-line analytical processing, began to be useful additions to a data warehouse, helping with the evolution from VLDB (very large database) to Enterprise Data Warehouse and Corporate Information Factory, and as, from the other end, data marts became more and more popular, market analysts and vendors expanded their offerings. Reporting vendors got into OLAP and OLAP vendors added simpler reporting tools. Some also added ETL to their mix, and ETL vendors tried to expand into reporting and analysis.
"Business Intelligence" is essentially a marketing term. First used, I believe by Gartner, in late '97 or '98. It really doesn't seem to have any one definition, as everyone is - after almost 10 years of use - still trying to apply it from their own unique perspective to their own set of problems or solutions.
As in the thread above, some wish to use it only for the technology, usually software, others wish to apply it to the analytic process, and still others to the results.
The technology may include the underlying RDBMS and MDDB, the data warehouse, operational data stores and data marts, the mechanism to get the data in a usable form into the tools [ETL], reporting tools, OLAP, pivot tables, and the presentation layer. More and more, I see data mining, portals, dashboards and predictive analytics added to the mix.
For our purposes, we define business intelligence as business processes and the integrated applications or individual tools serving those processes by providing data management, reporting and analytics to solve specific organizational and user community needs.
Contrary to assumptions of many small and medium sized business owners, business intelligence is not a fancy word meant for boardrooms of large corporates - it is as important for smaller businesses as it is for larger. In fact, considering that smaller businesses have exposure in just one or two areas and much lesser financial resources at their disposal, optimizing performance based on business intelligence becomes all the more critical.
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