As companies automate business processes, they should consider the meaning of information

First, one should be clear about the terms `data` and `information`. Data is the raw material you need to work with, and information is this material processed into something useful for the market. Quite simply, information should answer the question.

By way of analogy, you could use a supply chain management (SCM) model to illustrate how data moves through the chain to arrive at the customer`s desk; i.e. the month-end report to the CEO.

Taking the above definitions into consideration, businesses are therefore looking for an information solution which "takes raw materials, processes and manages it into the correct product that is useful to the market to answer the question".

Following a top-down approach of the information value chain based on SCM, we can model the BI systems architecture as follows :
* Information that answers the question - business intelligence;
* Correct product - business intelligence;
* Processes and management - information management model; and
* Raw materials - data extraction, transformation, loading and integration.

From this simple dependency chain, we can work out that in order for a BI solution to be effective, a suitable information management model needs to be in place. This model is pivotal to all aspects of the solution, since it understands where the data comes from and who uses it (useful for integration purposes). It also understands how to wrap and commoditise that information to assist in executive decision making.

However, the same problems encountered by a manufacturing supply chain are also encountered by the information value chain.

Traditionally, problems arise when BI and integration projects are started without a suitable information management strategy and model in place.

Businesses neglect this area because they regard the task of presenting their data in a common objective business language too huge.

Or, in most cases, architects are simply not aware of the implications of building a solution without such a strategy and model. Thus, the very reason to develop BI and integration solutions - to remove silos - is actually entrenched further, since the silos are now built and integrated into the BI and integration solutions from a subjective small picture view, and the cycle of misinformation continues.

Traditional information management solutions are merely large documents gathering dust on a shelf somewhere. They also fail to cater for the domain of semantics, which is the study of the meaning of the information you possess. Semantics is important because as we automate our business processes we cannot help but deal with the meaning of the information we are capturing and processing.

Part one of a two-part series on effective BI