From Data to Wisdom

The evolution of data

The following graphic is used to demonstrate the evolution of data at a holistic level.

In my storied and eventful career I have been both the savior and the victim of Business Intelligence. The battle has raged for years and the real victims are the customers who are trying to figure it out. Over time and after many scotch on the rocks I started to piece the pieces together.

To truly explain, I have to go back to the beginning.

Data Level

Is the simplest to explain, it is the raw 1's and 0's or the smallest information store. This could be someone's first name, location, city, postal code. An individual information component. For those spread sheet users, picture this as a single cell.

Management Level

You may know this layer as Content Management, Information Management or Document Management. They all mean the same at this data maturity level. When you take the raw data and start to draw relationships then it becomes information. For example: the city name is related to the city description file. The invoice detail is related to the invoice header by the same common invoice number. The content is related to a press release, the documents are related to a case file. Once you establish the relationships then information emerges.

Knowledge Level

You may know this layer as Knowledge Management. I was originally stumped on this term until I dug deeper. What I found was this. Once you take your information and start to see patterns emerging then you have knowledge. Patterns become key. When you can take different sources of information and established predictable patterns then the user has knowledge at their finger tips. Knowledge is power. You start to really work the results when solid proven patterns emerge predictably. When unpredictable patterns emerge you have data mining and that is even cooler information, but I digress.

Wisdom Level

This is the final layer and it is based on applying principals against the patterns. Like in life, this becomes the challenge. There a many people in life with the all the knowledge but do not practice a principled life and by definition are not very wise. Like most things in the Information Technology arena we are standing on the shoulders of giants. It takes time and experience to apply principals to knowledge.

In Conclusion

Data becomes information after relationships can be built and maintained. This information comes in the form of document management, content management and information management. Once this has been established, patterns emerge. Once this is done successfully, Knowledge Management is the outcome. Lots of work is being done in this regard.

The outer level, bring together all this information in clear patterns and applies principals. These principals are in effect wisdom. This is the newest area of work in data evolution. An example of this principled approach to data is this example. “A car has a flat tire and it will not start”. Data, information and knowledge tell us to repair the flat tire, however wisdom tells us to get the car started first. Without the car starting the tire conditions have no bearing on movement. I find both in society and technology we spend too much energy on the flat tire.

The more connected and the deeper our understanding the easier it is for us to reach the wisdom level.