Concept of Data, Information and Knowledge
Data management is a very lexically challenged discipline. A major part of that The words data, information, and knowledge provide a lexical problem. These three words are often overused, abused, and used interchangeably, such that their true meaning is often obscure. To begin overcoming the lexical difficulty and establishing a formal data management profession, these three words must be defined and utilized consistently.
Data
Individual facts that are difficult to understand and useless without context are referred to as data. They are commonly referred to as raw data. Datum refers to a single fact, while data refers to a collection of facts. A comprehensive, denotative definition of data in the singular form, beginning with Data, is not available, despite the fact that some people continue to use the term in that way. In reality, most meanings of “data” in the singular pertain to data sources.
Data, like deer or sheep, is an irregular word with context-dependent meaning. Data may be used to represent a collection of facts, just as datum can represent a single fact. However, the discipline of data management has enough linguistic challenges without considering data to be an irregular noun. As a consequence, data is plural, while datum is one.
Individual facts that are significant and easy to understand are considered data when put in context. They are not yet information; they are just raw facts with a veneer of meaning. In context, a datum is just one truth that has a deeper meaning connected.
Information
Information is defined as a collection of facts in context that are meaningful to one or more people at a given point in time. Information is more than simply facts in context; it must also be timely and relevant. Information is recognized as unique.
Knowledge
Knowledge is awareness, as well as the condition or actuality of being acquainted with something via association or experience. It refers to the understanding or comprehension of something, the awareness of something or its status, or the acknowledgment of a fact or reality. Knowledge is defined as information that has been preserved together with an understanding of its significance. Experience, investigation, familiarity, association, awareness, and/or comprehension are all examples of knowledge.
Both explicit and implicit knowledge exist. Implicit knowledge, also known as tacit knowledge, refers to information that a person keeps in their brain. It is not simple to distribute or transfer to others. Explicit knowledge, also known as formal knowledge, is information that has been codified, maintained for human use, and stored in various media (books, journals, recordings, presentations, and so on), such as a reference library or the internet. It may be simply copied to a variety of media and circulated worldwide.
Organizational knowledge refers to information that is valuable to the organization, along with experience and competence, and retained by the organization. It is contextual knowledge that allows one to understand what is significant and relevant to a business problem or issue, as well as what the company values. It entails assessing, analyzing, and synthesizing the importance of information to the firm and its prospective uses. Business intelligence is the outcome of rational data interpretation.
Knowledge management refers to the administration of an environment in which people generate implicit information, convert it into explicit knowledge, and then deliver it to the firm. The cycle in an intelligent learning organization continues because it lays the groundwork for more tacit knowledge. An expanding variety of applications, technologies, organizational structures, procedures, and policies are being created with the purpose of improving decision-making and creativity. It is a complete approach to discovering, transmitting, and evaluating information inside the firm. It is a learning culture that encourages knowledge exchange and the use of best practices for addressing business difficulties.
Some people perceive information improperly. One common misperception is that contextualized data and information are synonymous. When unprocessed data are given context, they become information. However, when information is seen as data in context, what differentiates timely and relevant information from irrelevant information becomes crucial.
The answer may include both important and irrelevant information. But knowledge can only be derived from relevant information; extraneous information cannot yield knowledge. As a consequence, meaning is imparted to basic data, transforming them into context-based knowledge that may or may not be applicable. Knowledge can only be obtained via relevant information.
Another common mistake is that information refers to any derived or summarized data. That assumption is incorrect since data are data regardless of how they were collected. They are not considered information since they have not yet become current or important.
Data in context is not informative unless it is current or relevant. Data, on the other hand, may be outdated or useless to one person but beneficial to another. As a consequence, the definition of information may be expanded. defined information is a collection of facts in context that are current and relevant to one or more people at a given time or for a defined period of time. General information is a compilation of contextualised data that may be beneficial to a large number of people at once or over time.
Because these terminologies have been specified, the cycle of data, information, and knowledge can now be defined. The diagram below depicts the data-information-knowledge cycle, which progresses from data to data in context, to applicable information (specific or general), to knowledge, and then back to data after that knowledge or information is stored.
Though many would want to dwell on the issue, knowledge and information stored become a firm asset and are managed in accordance with official data resource management concepts, norms, and processes. It makes little difference whether such data were initially unprocessed information, general or specific knowledge, or raw data. Everything that is retained is formally treated as data, is considered data, and is part of the organization’s data resources.
Both general and specialist information is considered part of the data resource, and it is managed and preserved in the same way as other data. When such facts become more current and important, they will be considered information. The same is true for comprehension. Knowledge that has been saved is considered as data and processed appropriately. Only when those facts are extracted as information, combined with experience, and preserved can they become knowledge once again.
Data refers to anything handled as part of an organization’s data resource, such as books on the shelf, papers on servers, raw data, saved forms or documents, stored reports, and so on. Others consider information or knowledge kept in storage to be data that may or may not be accessed as such.
Turning the situation around, all knowledge and information were formerly deemed data, regardless of whether they were stored in the organization’s data repository. Data became information if it was current and relevant. That information becomes knowledge when it is kept and combined with business experience.
These requirements exclude the creation of an information resource since timeliness and relevance are fixed. The term “information resources” refers to a set of technologies used to extract knowledge from data and give it to an organization. The bulk of implicit and tacit information that exists inside or is available to an organization is contained in human resources, resulting in knowledge resources.
Information assimilation overflow occurs when information comes in too fast for a person to assimilate and grasp. Because it is ambiguous, the term “information overload” is often misused. Information must be absorbed over a certain length of time, and the dissemination strategy must match this rate of assimilation.
Divergent information is defined as information that contradicts the receiver’s expectations. It might be the result of information derived from divergent data that offered conflicting information, information obtained from many sources with distinct structures, or contradictory information itself.
The fear of not knowing all that is or might be relevant in the future is known as information paranoia. This is a syndrome in which someone is obsessed with learning things just for the sake of knowing them.
Non-information refers to a set of data in context that are neither current nor relevant to the recipient. A recipient of data overload is flooded with contextualized information that is neither timely nor suitable. The recipient is flooded with irrelevant information that they do not want to receive.
Experts in data management must define language precisely and succinctly, and utilize it correctly. One step toward overcoming the lexical problem in data resource management and developing a professional data management profession is the establishment and proper utilization of basic language…