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DIKW Pyramid Explanation using Real Life Use Case
DIKW pyramid defines the relation between data, information, knowledge, and wisdom. Each phase of the pyramid adds meaning to the data by answering questions about it. The higher we climb the pyramid, the more questions we respond.
There are different basic examples for each layer of DIKW pyramid but most of them have no sense for real life. To clarify this issue, the phases of DIKW pyramid are explained using Sales Data in this article.
DIKW - Sales Use Case:
1) We define data as simple facts that are unorganized.
In the use case the data entities like products, customers, sales representatives can be defined data alone.
Note: If we consider a data entity as a table in a database management system, this entity can also be considered as information.
2) Information is structured, organized, and processed data, which makes it relevant and useful.
Sales data is information which is the result of relation between products, customers, prices, campaigns, and sales representatives.
In addition, another example for information can be a report like "Monthly sum of sales grouped by each product".
3) Clustering similar customers by using statistical methods and obtaining these clusters is knowledge.
At the end of clustering, we get the clusters (customer segments) and know that how these clusters are constructed. Here we can answer the question “How?” since we know the logic of algorithm (E.g., K-Means, DBScan).
4) Wisdom is making the best possible use of the available knowledge. It would be also correct to define wisdom as an ability, and it lets you do things and take actions with knowledge.
Using different features and different methods (E.g., K-Means, DBScan) we can obtain different clusters. With a domain knowledge we can choose the best clusters to take some actions. For example, we can organize campaigns for customers in some clusters.