Before we know the relationship between data, information and knowledge, firstly, we need to understand their definition. Date could a the unanalyzed, raw, unorganized, unrelated materials is used to derive information after analyzation. Basically, data is facts that we observe, including symbols, images, numbers and characters. These original data is collected and ready for analysis to establish the information. Data left alone isn’t informative and could be relatively meaningless. However, it gains a purpose to analyze and form information. After receiving data, we can process, analyze, and organize those data to a different set. The data is becoming useful for people after these procedures above. Once data is processed and gains relevance, it will become information that is certain, useful and reliable (Santos, Piechnicki, Loures, & Santos, 2017). We could say that information is a kind of prepared data that has been aggregated, organized and processed into a more human-friendly format that provides more context. Information is often delivered in the form of data reports and dashboards. Knowledge means the awareness and familiarity of a person, idea, events, issues, ways of doing things, which is received by perceiving, learning, or discovering. A combination of information and experience leads to knowledge that has the potential to draw inferences and develop insights.
Currently, the business world has been changing fast. The information system needs to be updated in time to adjust the innovation and rapid change of situation. Organizations of this age are faced with the major challenge of dynamic stability at all different levels. It could be said that this new age is like a stage for organizations that have been able to take control of the amazing capabilities of knowledge and use them to gain progressive, competitive advantage (Paghaleh, Shafiezadeh, & Mohammadi, 2011). Now, most of the companies meet different dimensions of dynamism and uncertainty. Therefore, the organization needs a more efficient system to analyze the data and information. For example, managers need to understand a company’s culture better and user’s specific requirements. Otherwise, it needs to improve communication between different departments.
Reference
Li, D., Landström, A., Fast-Berglund, Å., & Almström, P. (2019). Human-Centred Dissemination of Data, Information and Knowledge in Industry 4.0. Procedia CIRP, 84, 380–386. https://doi.org/10.1016/j.procir.2019.04.261
Dos Santos, C. F., Piechnicki, F., de Freitas Rocha Loures, E., & Santos, E. A. P. (2017). Mapping the Conceptual Relationship among Data Analysis, Knowledge Generation and Decision-making in Industrial Processes. Procedia Manufacturing, 11, 1751–1758. https://doi.org/10.1016/j.promfg.2017.07.305
Paghaleh, M. J., Shafiezadeh, E., & Mohammadi, M. (2011). Information technology and its deficiencies in sharing organizational knowledge. International journal of business and social science, 2(8), 192-198.
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