Data VS Information VS Knowledge | Elium

The words data, information and knowledge are often thrown around as substitutes for each other. However, these three terms technically mean separate things. You might ask, “Why bother being pedantic with the terms? What difference does it make?” Well, if we want to manage knowledge, we need to clarify the terms and understand the different meanings at play. 

Once we define the basic terms and relate them to each other, we can comprehend their implications for practice and see their importance to our company processes. 

Data, Information and Knowledge

There are three generic things we usually refer to when we use the words ‘data’, ‘information’ and ‘knowledge’. First, when we talk about things that we know about: concepts, facts, and methods that we are familiar with. Second, when we deal with practical know-how: applying our grasp of concepts, facts, and methods to create action or make things happen. Third, when we refer to a body of knowledge: accumulated knowledge in books and other forms of documentation. 


Free Guide: Company-wide knowledge sharing


In their in-depth investigation of working knowledge, Davenport and Prusak (1998) established distinctions between data, information and knowledge. Their definitions of data, information and knowledge are as follows:


Data are raw facts and figures with no fundamental meaning. Data plainly reports part of a situation without providing an interpretation. It is an unprocessed form of knowledge that doesn’t convey value or significance. For data to have some useful meaning, it has to be organised, analysed and interpreted. In the context of an organisation, “data are most usefully described as structured records of transactions.”

Data can be:

  • Quantitative: when data can be counted or measured like cost, weight, and volume.

  • Qualitative: when data describes things like name, color, and shape.   


On the other hand, information is processed data. It is organised, classified, structured and provides meaningful and useful context. In contrast to data, information has meaning. “Data becomes information when its creator adds meaning. We transform data into information by adding value in various ways.” Here are several important processes that convert data to information:

  • Calculation: data are mathematically or statistically scrutinised

  • Categorisation: data are sorted into groups or classes

  • Condensing: summarising data to be more concise

  • Contextualising: gathering data for a purpose

  • Correcting: editing errors out from the data


Davenport and Prusak proposed a working definition of knowledge framed in a practical sense of organisational knowledge that it is “broader, deeper and richer than data or information”:

Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms.

This idea of knowledge is an amalgamation of information, that knowledge is a state of being, exists outside of the ‘knowers’, and has the capacity to effect action. This leads us to the two basic types of knowledge and the concepts of explicit, implicit, and tacit knowledge:

  1. Knowledge that is contained within a person alongside the person’s faculty to act on that knowledge

  2. Knowledge that is communicated and documented

Explicit, Implicit, and Tacit Knowledge

Here is a simple diagram by Nickols (2010) to distinguish explicit, implicit and tacit knowledge. 

Explicit Knowledge

Explicit knowledge is knowledge that is easily expressed, communicated and captured in text documents, diagrams, illustrations, and product specifications among other things. Examples of explicit knowledge includes scientific formulas, computer proograms, industry standards, and company best practices. It is “formal and systematic knowledge” (Nonaka, 1991).

Implicit Knowledge

On the other hand, implicit knowledge is displayed knowledge that can be captured. A simple example would be someone performing a task and how they execute that task is a display of implicit knowledge. Identifying and capturing that implicit knowledge can turn it into explicit knowledge that can be used across similar tasks.

Tacit Knowledge

Tacit knowledge is less tangible and more difficult to articulate and transfer. It is knowledge in the form of individual skills, wisdom, experience and ideas. Unlike explicit knowledge, tacit knowledge is usually passed on through exhaustive exposure to and continuous practice with the person of knowledge. Everyday life examples include language and intuition – knowledge that is harder to systematise or automate. 

Declarative and Procedural Knowledge

Psychologists also classify knowledge into declarative and procedural. But to touch on the terms briefly, declarative knowledge is practically similar to explicit knowledge as it is knowledge that describes facts, methods and procedures. 

Meanwhile procedural knowledge leans more towards the knowledge of doing something. Some experts in the field equate this to implicit knowledge while some view it as tacit knowledge. Regardless of where you stand in this difference of opinion, the fact remains that procedural knowledge is difficult to articulate and document in the form of text, diagrams and so on.

Practical Use of Knowing the Terms

Why did we have to go in depth with all the different terminologies? It all comes down to effectively identifying what to capture, share and transfer within your company. Understanding what data, information, knowledge and the types of knowledge are is fundamental to driving your organisation’s success. 

Maximise Your Company Potential Through Efficient Knowledge Management

Your company’s success depends on how you catalog and utilise all the data, information, experiences, and random knowledge you have acquired through individual employees and as an organisation. Filing explicit knowledge is not enough. To remain competitive, it is imperative that your company has the means to transfer and translate tacit knowledge of high-performing employees to their peers.

Elium is an easy online tool that can help your team effectively capture individual knowledge so they can store and share critical know-hows of their work process. Turn data and information into actionable knowledge through Elium’s unique collaboration space where employees can share best practices and individual experiences as a learning point for their peers. 

Download our company-wide guide to find out how Elium can empower your organisation today. Or sign up for a free trial to start building a knowledge-driven workplace.

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