On Data, Information and Knowledge
Many people confuse knowledge with data and or information.
A commonly held view is that data represents raw facts, information is organised data and knowledge is formatted information (Raisinghani, 2000).
Data is a set of distinct, objective facts about events. It is factual information and is often in numerical form. It can also be structural records of transactions. It provides no judgment or interpretation, no sustainable basis for action, and it says nothing about its own importance or relevance.
Accordingly, information is data organized and presented by someone as a message; usually in document form, audio or visible communication; has a sender and a receiver. It is meant to make some difference in the receiver’s outlook or insight. Information moves around organisations through hard or soft networks.
Hard networks have visible and definite infrastructure; wires, delivery vans, satellite dishes, or post office (examples include; emails, snail mail, and internet). Soft networks include; opinions, ideas, rumors, economic projections, statement of management’s future plans, and market commentaries, (Stein, 2002).
Even in the 21st century, many organisations are mostly unaware of the potential value of the corporate information and data they hold.
Knowledge on the other hand is information read, heard, or seen, and understood. It can be termed as a fluid mix of framed experiences, values, contextual information, and expert insight that provide a framework for evaluating and incorporating new experiences and information. It originates in the minds of people and in organisations; it often becomes embedded not only in documents or repositories but also in organisational routines, processes, practices, and norms, (Davenport & Prusak).
Knowledge can also be likened to a living system, growing and changing as it interacts with the environment. Critical to this argument is the concept that knowledge does not exist outside of an agent or knower, and is indelibly shaped by one’s needs as well as one’s initial stock of knowledge, (Fahey & Prusak).
The objectives of knowledge management are to make an enterprise act as intelligently as possible, to secure its viability and overall success, and to otherwise realise the best value of its knowledge assets (Wiig 1997). Therefore, the analysis and management of data and information can be transformed into knowledge that in turn can be used to ‘gain business benefits such as a competitive advantage.’
In the 21st century, organisations must understand the importance of the use of generated data and/or information to support their business activities. Of particular interest is how they navigate the journey from data-to-decision.