DIKW model

• Data is a set of disconnected facts and symbols (numbers, words, visual data). It sits at the bottom of the hierarchy and is the raw material from which something valuable can be derived. Data by itself provides no value.
• Information is data grouped by meaning. At this level, the basic building blocks of facts form connections. Unlike data, information is useful because it describes processes and phenomena. It answers basic questions: "who?", "what?", "when?", and "how many?". Information alone is not enough to solve problems.
• Knowledge is the result of filtering information and processing it so that conclusions can be drawn. Interconnected facts form a complete picture of a phenomenon or process that can be used to draw conclusions (if A, then B).
• Wisdom is the top of the pyramid. At this stage of data processing, understanding is added to knowledge. If information answers the question "what?" and knowledge answers "how?", wisdom tells us "why?". Understanding lets us go beyond the phenomenon or process we are studying and use it for broader goals.

With each level, data becomes more structured and usable.

Even before the model was used in knowledge management, its essence was expressed by the poet T. S. Eliot in "The Rock," where he suggests that information is not yet knowledge, and knowledge is not wisdom. With the arrival of the information age, the amount of data began to grow rapidly. Large volumes of quantitative and qualitative variables open up wide opportunities but have no value in themselves. To use them for your own purposes, you need to understand what to do with them.

The DIKW model is one of several models that help extract something valuable from the chaos of data. The wisdom gained by applying this model benefits organizations that provide IT services. Raw data says nothing about users, their behavior, or how they interact with services. Only by going through all the stages and reaching the top of the pyramid can you use user data to create a product people actually need.

Russell Ackoff, a researcher of systems theory and management, described this hierarchy in his 1989 paper "From Data to Wisdom". He did not present the model as a pyramid. He saw it as a continuum whose first three stages belong to the past. Data, information, and knowledge make it possible to describe existing processes and relationships, but only wisdom allows you to predict and forecast. That is why creating something new is impossible without the final stage of data processing.

The main area where the DIKW model is used is knowledge management and information management. Big data and data visualization follow a similar model. A knowledge management system is a set of management procedures, repeated on a regular basis, designed to make the collection, storage, distribution, and use of information valuable to the company more effective. Knowledge management plays a key role in service transition (ITIL).

Applications of this model rely on semantic technologies (Linked Data, semantic graph databases) that can build connections between scattered heterogeneous data and extract useful knowledge from existing facts.