Saturday, September 16, 2006
Solving the All-Data Problem #1: The Data Optimization Pyramid
The figure on the right depicts the "data optimization pyramid". This is the key scoping strategy that all organizations should use to apply reasonable management techniques to their data by first realizing that "all data is not equal". This means that you do not apply management techniques to all your data because not all of your data is meaningful or relevant. The key is developing an understanding and management strategy to allow relevant information to rise to the top. This may mean that you apply some brute force techniques to the Unmanaged data (like unstructured data) in order to assist you in the "bubbling up" process. But on the other side of the coin, labor-intensive tasks like tagging are reserved for a smaller subset of the data. Ok, you should have noticed that the pyramid is not complete ... here is where I need your help to find a good name for the top tier. At the top is critical data that you want to automate rules against, require a guaranteed level of fidelity or is highly relevant to a particular high-value ad-hoc community of interest. So, what do you think that top-tier should be called?
Some options:
- Augmented Data
- Refined Data
- Formal Data
- Critical Data
Comments very welcome ...
