Upgrade to remove ads
Only $2.99/month

DIKW (Data, Information, Knowledge, Wisdom)

Terms in this set (8)

Data
symbols. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself.
-Facts
-Pieces of information
-A set of values of qualitative or quantitative variables
Information
data that are processed to be useful; provides answers to "who", "what", "where", and "when" questions. Data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.
- is a meaningful message created by interpreting and analyzing data
Knowledge
application of data and information; answers "how" questions. The appropriate collection of information, such that it's intent is to be useful.
Understanding
appreciation of "why". It is the process by which I can take knowledge and synthesize new knowledge from the previously held knowledge. Able to synthesize new knowledge from previously stored information and knowledge.
Wisdom
evaluated understanding. It calls upon all the previous levels of consciousness, and specifically upon special types of human programming (moral, ethical codes, etc.). It beckons to give us understanding about which there has previously been no understanding, and in doing so, goes far beyond understanding itself. It is the essence of philosophical probing. The process by which we also discern, or judge, between right and wrong, good and bad
Structured Data
• Highdegreeoforganization
• Structuredintotables
• Easytoanalyzeandvisualizedata, particularly when its size is not too big
• Calculatestatisticsofquantitative (structured) data without special data processing to organize it
• Examples:valuesofquantitativeand qualitative variables organized in spreadsheets
Unstructured Data
• Structuredintotables
• Easytoanalyzeandvisualizedata, particularly when its size is not too big
• Calculatestatisticsofquantitative (structured) data without special data processing to organize it
• Examples:valuesofquantitativeand qualitative variables organized in spreadsheets
• Lowdegreeoforganization
• Cannotbestructuredintotables
• Needspecialtechnicalsolutionsto analyze and visualize data in order to extract meaningful information
• Cannotcalculatestatisticsof (unstructured) data as it is
• Examples:videos,audios,pictures and documents
Data Lifecycle
1. Collecting or Sharing Data
2. Storing and Processing Data
3. Analyzing Data
4. Preserving Data
5. Discarding or Reusing Data
THIS SET IS OFTEN IN FOLDERS WITH...