Distinguish between Data, Information, and Knowledge
- What is Data? 🧩
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- Data are raw facts or observations that are considered to have little or no value until they have been processed and transformed into information.
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- Unrelated items of data are considered as noise.
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- Examples: 📅 Today’s date, records of a business transaction 🧾, a single website visit 🌐, or accounting transaction 💵.
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- What is Information? 📊
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- Data that have been processed so they are meaningful.
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- Data that have been processed for a purpose.
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- Data that have been interpreted or understood by the recipient.
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- Examples: Bank statement 🏦, sales forecast 📈, graphs of trends in website visitors 📉.
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- What is Knowledge? 💡
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- Knowledge can be thought of as the combined result of a person’s experiences and the information they possess.
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- Information + Experience = Knowledge.
- Tacit Knowledge: 🧠
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- Intangible knowledge that is intuitive and not recorded since it’s part of the human mind.
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- Its factors include perceptions 👁, beliefs 🤔, values, intuition, and experience.
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- Examples: Skills like how to swim 🏊♂️ or ride a bike 🚴♂️.
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- Explicit Knowledge: 📚
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- Knowledge that can be readily expressed and recorded within information systems.
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- It tends to be highly detailed, formal, and systematic.
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- Examples: Employee handbooks 📖, user manuals 📝.
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To Sum Up: 📝
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Data 🧩: Little or no value → Process ⚙️ → Information 📊: Meaningful, understood, interpreted by a decision-maker 🧑💼 → Combined with Experience 🧠 → Knowledge 💡.
- Knowledge can be:
- Tacit 🧠: Informal, experience-based, perception-driven.
- Explicit 📚: Formal (written), systematic, detailed.
- Knowledge can be:
Understanding the difference between data, information, and knowledge is essential in today’s data-driven world. Data is the starting point, information is processed and structured data, and knowledge is the combination of experience and information. These concepts help individuals and organizations make better decisions and work more efficiently.
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