According to my reasoning based on the core components of data analytics, I believe data can be treated as human. Let’s go through the components one by one:

  • Descriptive Analytics
    It helps to answer the question about what has happened — just like how humans think and summarize past events. Recalling what we did yesterday or last year helps us understand the outcomes. Descriptive analytics works the same way by summarizing historical data.

  • Diagnostic Analytics
    This provides an answer to the question “Why did an event happen?”
    Just like we visit a hospital to understand the cause of an illness or question the reason behind a health issue, data also examines the cause of anomalies in trends. It helps us understand the why behind the what.

  • Predictive Analytics
    It provides answers about future occurrences. Data has an intuition or foresight that forecasts future outcomes based on past trends. It’s like having a sense of what is likely to happen next.

  • Prescriptive Analytics
    By providing answers to what actions should be taken to achieve a goal, it reflects judgment or decision-making. Just as humans evaluate different options and choose a path, data gives us actionable advice based on predictions and diagnostics through prescriptive analytics.

  • Cognitive Analytics
    This is where data almost behaves like a human — because it attempts to draw inferences from existing data and adds the findings back into the system. This allows it to learn, adapt, and improve over time, just like human intelligence.

Conclusion
From these five core concepts of data analytics, even though data lacks emotion, morality, or consciousness, it can simulate thinking. While it doesn’t feel or understand the way we do, I believe treating data as human will help us gain better understanding and deeper insights.

✅ Understand data more intuitively
Instead of just seeing raw figures or trends, you begin to relate to them.

Descriptive = storytelling

Diagnostic = reasoning

Predictive = foresight

Prescriptive = advice

Cognitive = learning

This human framing turns data from something technical into something relatable.

✅ Ask better questions
Just like when talking to someone, treating data as human makes you ask:

“What are you trying to tell me?”

“Why did you do that?”

“What should we do next?”

“How can you improve?”

Those questions lead to deeper analysis and better insights.

This post was inspired by the Data Analyst learning path on Microsoft’s Career Essentials course and the image is generated by chat gpt.