The answer is Logs.

Logs are the only metadata that exists today that:

1. Is widely available
2. Is 100% collectable
3. Is 100% storable
4. On which we can run intelligent reports
5. Allows us to understand the kinetics aspects of this ever-changing data

For example logs allow us to understand if a data has had several versions and iterations and, for each iteration:

1. Who created, modified or deleted the data
2. When was the information created/modified/deleted
3. What device was used for the creation/modification/deletion
4. Was that creation/modification/deletion authorized
5. It even gives us some context information that we can use in order to infer some additional information

In fact, properly used logs allow us to understand a lot about how the data came about and the different iterations of this data.

Granted, this is not as good as the brain’s holographic capabilities to keep and process so much history and context about each version and iteration of data, but in the context of Information Technology it is the best we can do today.

And a good way of managing logs in an Information Technology framework would certainly help us emulate the way our brain works.

A good Log Management solution is a solution that collects 100% of the logs 100% of the time, stores all this data and provides intuitive searching and reporting mechanisms to better understand some aspects of the changes applied to the actual data. If this solution provides for alerting mechanisms to flag for unauthorized or otherwise unusual behavior then it’s even better.

These solutions can help us put the animation back into what has traditionally been a one-dimensional approach to a multi-dimensional issue.

And data got much closer to information.

And information got closer to knowledge. And knowledge got closer to intelligence.

Thanks to logs and thanks to Log Management and Intelligence Solutions.

• From Data to Information to Knowledge to Intelligence
• An Introduction to JDOM Part 2 of 2
• Integrating Enterprise Information on Demand with XQuery - Part 2