DIKW Model |Data Information Knowledge Wisdom|DIKW Model in ITSM

by Kishan Tambralli

Under the Service Transition Segment of ITSM Knowledge Management, the DIKW  model is a fundamental concept. When we accumulate raw data, it comes in a topsy-turvy manner. DIKW pyramid explains how the data can be refined and transformed into Information, Knowledge, and Wisdom with a constituent of actions and decisions.


Prologue to DIKW Pyramid:

Under the Service Transition division of ITSM Knowledge Management, the DIKW model is a critical component. The DIKW pyramid is seen from experience as a method of researching, communicating, connecting, and reflecting. Data, information, knowledge, and wisdom, are depicted as four distinct layers in the DIKW Model (Data-Information-Knowledge-Wisdom). Data is the base foundation of the pyramid, then the next layer is Information, the third layer is knowledge, and the fourth layer is wisdom, the apex. DIKW model is widely used in Information Science and Knowledge Management-ISKM. Theoreticians widely use DIKW Model in library and Information Science.

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It is an approach to determine the unrefined or unorganized external information such as figures or characters that are yet to be explained. For instance, without a framework, data can seem little.  Example: 25012012 is a series of numbers without manifest importance. However, if we view it in the framework of this, it is a date we can easily identify 25th January 2012. By adding circumstances to the numbers, now adds more value.


Information is the second building block of the DIKW hierarchy model. In this, the data has been purified free of errors and processed in an approach that makes it easy to evaluate, envisage, and examine the inputs for a specific purpose to establish organizational needs. The essential aspect of information management is apart from responding to queries; it also helps identify organizational contexts.

Subject to the purpose, information processing will entail different actions such as aggregation to ensure the accumulated data is relevant and accurate (Validation). For instance, we arrange the information in an approach that reveals the link between diverse apparently different and unconnected data points. More specifically, we can examine the Dow Jones Index's output by constructing a graph of data points for a specific time span based on the information at each day's closing.

We may extract valuable information from the data and make it more beneficial for us by asking important questions about "Who, What, Where, and Where.” But when we get the question as to “How,” then what leaps information to Knowledge.

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Knowledge is the third phase in DIKW Model. It represents a collection of accurate data. This phase seeks to find the answer to the “How” query. “How” the information is obtained from the accumulated data relevant o our goals? “How” the pieces of information are connected to other pieces and add more meaning and value? And “How” can we apply the knowledge aspect to accomplish our goal?

Knowledge is commonly the edge that organizations have over their enterprises. As we reveal the relationships clearly stated as information, we get profound insights that take us higher the DIKW Model. When we utilize knowledge and insights achieved from the information to make dynamic decisions, we can say ha we have reached the final phase – the “Wisdom” step of the DIKW model.


Wisdom- This is the utmost level in the DIKW hierarchy model, and it seeks to respond to the queries related to “Why do something? As well as “What is best? In other words, “Wisdom is intelligence in action,” to put it another way. Knowledge and Wisdom are linked to the present and future in achieving goals.

 It is the last phase of the DIKW hierarchy model. It is a method to get the final desired results by calculating through the assumption of knowledge. It considers all the output of preceding levels of the DIKW Model and applies it through a special form of human programming (like moral, ethical codes, etc).

How Businesses and Organizations Progress Through the Knowledge Model:

Employing Semantic Technologies such as Linked Data and Semantic Graph Databases is an easy and quick way for businesses and organizations to complete the steps of the DIKW Model from Data to Information to Knowledge to Wisdom. These technologies may establish links between diverse and miscellaneous data and conclude knowledge from available and existing facts. With this new insight, businesses and companies can ascend the wisdom mountain and gain a competitive advantage by using data-driven analytics to aid their business decisions.

DIKW Model in ITSM:

DIKW Model is the ITSM v3 version of Knowledge Management. It is described as a growth path for comprehension or understanding. This concept is a virtuous one as it builds on the traditional view that Data becomes more beneficial once it is refined and processed into information. The DIKW pyramid applies to ITSM as ITSM comprises knowledge in IT. In the course of day-to-day operations and service delivery, critical data is produced. The data is in the form of a metric function, and the data is also generated during the course of conducting business research involved in responding query by the Help Desk. Data after primary generation become information when examined, contextualized, and exhibited in a dashboard or report.  This data becomes more beneficial when examined and easy to make data-driven decisions. Finally, this knowledge may become Wisdom when used by individuals are utilized with insight to resolve difficult challenges or to establish unique solutions.

One fundamental aspect of ITSM is to computerize as much information as realistic to assist support service work. Service delivery comprises all activities offered for IT Operations activity. In the concept of ITSM, knowledge not only internalizes for organizational application but also changes the way processes are carried out as a result of previously existed documented knowledge.

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