Bill Inmon has recently posted an article on "Why has Data Mining struggled so much?"
The article discusses 7 diferent reasons why data mining has struggled, as it has been around for a very long time.
The main points are
1. We have been waiting a long time for it to become available in a usable way
2. Data mining is considered an academic focused with very few practitioners. But this is become less so
3. Data mining requires a different set of skills. Yes you need data management skills but you also need some data mining skills. I will be making a posting focusing on the skill sets required for data mining in the coming weeks.
4. Some industries and application areas are more suited to data mining than others. The difficult is in identifying suitable projects.
5. Data for Data Mining is unclean. Not if you use a data warehouse. Idealy an organisation who has a matur-ish BI infrastrucure will benefit must from a Data Mining project
6. Data is incomplete. Yes you may need to enrich the data from various sources. But again if you have a Data Warehouse you will have most of these
7. Approaches to data mining inadequate. Alot of the approches to data mining projects as based on its statistical history. New problem areas are evolving all the time and we can use data mining in lots of different way.
To view Bill Inmon's article - click here.
To view our 2 training courses on data mining - click here