The Data, Information, Knowledge, Wisdom $($DIKW$)$ Pyramid has significant meaning to data analytics and the future of datafication. The pyramid model defines the life cycle of filtering raw data to extract and adapt information to become knowledge and wisdom.

Raw data contains noises and unstructured patterns, which might be valuable messages but require resources to transform the raw data into facts. The second layer of the pyramid is information. For example, raw data is everything we can capture with our senses$,$ or devices collect raw data on our interactions and behaviors on social media. Information is the output after conversion from raw data by adding context and retrieving patterns. Information is the answer to the question "what," "when," and "who." An example is when the phone sends us a notification for screen time, which means how long we spend on the phone periodically. Also, information is metrics used in the evaluation of the performance of a process or system. The third layer of the pyramid is knowledge. Knowledge is the answer to the question "how." In other term, knowledge is the combination of several pieces of information. To achieve this level, the data analysts must analyze and interpret the metrics or measurements they established in the layer of information. For example, when comparing two measurements at two different times, the analysts must express the messages behind those figures. Finally, the highest level, wisdom, is the answer to the "why" question.

By applying the knowledge along with other deliberations of contexts, wisdom allows the users to unfold hidden objects and explain "Why does this matter?" An example of wisdom is expanding knowledge to other aspects, which might have less or no connections between two events. Understanding the pyramid allows the analysts and the team to leverage and take advantage of the big data to become wisdom. Do you agree or disagree with this? Why