Author: Yaki
In the AI era, the value of data is being redefined, but one core principle has never changed:
Good data leads to good results. There are no shortcuts, and that has never changed.
What counts as good data?
In today’s information-saturated world, many people struggle to tell whether data is authentic. AI-generated content is everywhere in our lives. If we can’t trace data back to its source, what we consume may be riddled with deception!
A four-step framework: from data to results
1. Trace the source — find authentic data
Don’t blindly believe every piece of data you see. If the data is useful to you, be sure to trace it back to its source, find where it came from, and verify that it’s authentic!
2. Reconstruct — identify the definition as it was originally intended
For example, many people have heard the saying:
- “Of the three forms of unfilial conduct, having no descendants is the worst.”
- “If a person doesn’t look out for themselves, heaven and earth will destroy them.”
I believe the explanations of these two phrases have been etched into the minds of most people, but most people have never truly traced their origins or reconstructed their real meaning. Everyone repeats them by word of mouth, and as they get passed along, they eventually take on a different meaning!
3. Discern — determine the value of data
Truly valuable data and insights are never just a passing trend or a momentary emotion. They stand up to scrutiny and withstand the test of time.
Don’t let fleeting illusions lead you astray or short-term traffic numbers fool you. Let information and data settle over time, filtering out the hype and falsehoods. What remains is what’s truly worth believing in and using.
4. Results — only then can data produce good results
Once you’ve completed these three steps—tracing the source, reconstructing, and discerning—the information and data you have will be clean, authentic, and full of substance.
Only by using data like this to make decisions, create, power AI, and guide your life can you achieve reliable, positive results with lasting value.
Conclusion
The saying, “At first, a mountain is a mountain; then, a mountain is no longer a mountain; finally, a mountain is once again a mountain”
describes a process of “knowing what is” → “understanding why it is” → “finally, bringing it all together”
It is also a journey from believing appearances, to unpacking what lies beneath, and then returning to what is real.
The same is true of data, understanding, and life.
I’m Yaki. Good night 🌙