It’s been a little while since I’ve posted anything on this blog so thought I better write something. I’ve currently re-writing my enterprise data model book so have included a clip below. Please be aware the book is still in draft form.
Information and Data
Data is individual facts that have a specific meaning for a given time period. Data can be at the atomic level (for example ‘date of birth’) or derived (such as ‘age’). Therefore if we take a person called John Smith who is born on the 1st September 1999 we have three pieces of Atomic Data (first name, surname and date of birth) and two pieces of Derived Data (full name and age). The full name is a combination of the first and surname whilst the age is derived from the date of birth.
Let’s try explaining this using a different approach. Imagine we have the number 110110, it’s not immediately clear what it means. It could be the date 11th January 2010 or 1st November 2010; depending on which side of the Atlantic you reside. It doesn’t have to be a date what about a binary number which represents 54 or an actual amount of a transaction 110,110 with the currency unspecified.
DIKW stands for ‘Data, Information, Knowledge and Wisdom’. It represents the continuum from Data all the way to Wisdom. The diagram below shows the linkages between wisdom, knowledge, information and data.
Explicit knowledge can be (or has been) codified, documented or explained. Tacit knowledge on the other hand is knowledge that is difficult to explain verbally or in a document or for that matter to store in a database. For example Maidenhead is a town in Berkshire (in the United Kingdom) is a piece of explicit knowledge. The ability to speak English is much harder to explain and can be considered as tacit knowledge.