The Pyramid of Knowledge and DIKW Hierarchy

[shuklarani621]

We live in an era where we are exposed to a huge amount of data on a daily basis and in order to understand it, it is necessary to hierarchize and interpret the information. This is how the term Knowledge Pyramid, or as it is also known, the DIKW Hierarchy (Data-Information-Knowledge-Wisdom) came about.



Continue reading to better understand how the concepts of Data, Information, Knowledge and Wisdom relate to each other.

Main features of the knowledge pyramid


The knowledge pyramid is a hierarchy of concepts widely jamaica number dataset in data analysis, information science, archiving and information management. One of the first researchers to study the subject was Russell Ackoff, in the 1980s.



The North American theorist said that data alone does not have total meaning, as it needs to be interpreted in order to have value and become, in fact, information. Knowledge, therefore, is the set and understanding of this information.

Data are factual, qualitative or quantitative records, and information is the contextualization that gives relevance and purpose to this data. Therefore, the organization and standardization of information is what makes knowledge possible.



Wisdom is the result you achieve through the analysis of the different scenarios presented so far. In other words, one aspect depends on the other, so it is important to maintain this sequence of the knowledge pyramid.

Knowledge and artificial intelligence


Machine learning systems perform automatic processes to understand information, which helps organizations that need to deal with massive amounts of data. In this case, wisdom focuses on people and how they use the knowledge available to make the best decisions for the company.



In this context, artificial intelligence is a field that has been increasingly developed, as it enables a greater capacity for processing databases and obtaining knowledge at a lower cost, since machines can “decipher” algorithms that help us with more accurate predictions.



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Challenges and application of the knowledge pyramid
The main challenge of the knowledge pyramid is to provide an effective method for organizations to generate wisdom efficiently. Companies need to structure the best way to obtain data and relate it, in order to generate information and transform it into in-depth knowledge of their activities.



An example where the DIKW hierarchy can be implemented is in the analysis of cases of the new Coronavirus in the country. The data alone only presents numbers, which when interpreted over a period of time, can identify the part of the population that is most affected, in which regions, age group, gender, etc.



This information produces knowledge and contributes to the development of problem-solving strategies and decision-making, such as in relation to quarantine and vaccine development.



Information is a more elaborate perspective of a given piece of data, and knowledge produces the strategy and how to put the information into practice. Wisdom is the why, the reason, and the perception one has of the whole, that is, the results obtained.

[yadaysrdone]

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