The Data-Information Hierarchy is a fundamental concept often illustrated as a sequence:
Data --> Information --> Knowledge --> Understanding --> Wisdom
Or it is sometimes shortened to 4 steps, omitting Understanding. But, in fact, there are two predecessor steps: chaos and symbol. These concepts have been discussed in prior blogs:
In this paradigm, "Chaos" is akin to the initial state of a newborn baby, where there's a lack of comprehension regarding quantities or values. It's a stage of perceiving the world in terms of big and small without a deeper understanding.
Next comes "Symbol" (or symbolic representation), marking the early steps of quantification. Symbolic representation and quantification concepts are the precursors to "Data."
Expanding upon this Data-Information hierarchy, we can refine it into seven distinct steps:
To further clarify this Data-Hierarchy concept for technologists, let's provide a concise breakdown of the five primary steps:
- Data and Information: This phase revolves around "Knowing What." It involves collecting and organizing data, shaping it into meaningful information that can be readily understood.
- Knowledge: Here, it's all about "Knowing How." Knowledge represents the application of data and information, allowing you to navigate and utilize what you've gathered.
- Understanding: Delve into the "Know Why" realm. Understanding goes beyond surface-level knowledge; it's about grasping the underlying reasons and principles behind the data and information.
- Wisdom: This is where you "Use It." Wisdom arises from a deep understanding and empowers you to make informed, strategic decisions based on your knowledge and insights.
In essence, this Data-Hierarchy paradigm serves as a foundational framework for technologists, guiding them through the progressive stages of data transformation and interpretation, ultimately culminating in the wisdom to apply that knowledge effectively.