data-science-module-1.html

---
layout: default
title: What Is Data?
permalink: /learn/data-science/level-1/module-1/
description: Learn what data is, how observations become records, and why data is a representation of reality rather than reality itself.
---

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<main class="lesson-page">

  <section class="lesson-hero">
    <div class="lesson-container">

      <div class="lesson-breadcrumb">
        <a href="{{ '/learn/' | relative_url }}">Learn</a>
        <span> / </span>
        <a href="{{ '/learn/data-science/' | relative_url }}">
          Data Science Academy
        </a>
        <span> / </span>
        <a href="{{ '/learn/data-science/level-1/' | relative_url }}">
          Level 1
        </a>
        <span> / Module 1</span>
      </div>

      <span class="lesson-eyebrow">
        Data Science Academy · Level 1 · Module 1
      </span>

      <h1>What Is Data?</h1>

      <p>
        Data begins with reality, but it is not reality itself. It is a
        recorded representation of people, events, measurements, systems,
        behaviors, or processes.
      </p>

    </div>
  </section>
  <section class="lesson-section lesson-overview-section">
  <div class="lesson-container">

    <div class="lesson-heading">
      <span class="lesson-label">Lesson overview</span>
      <h2>What you will learn and create</h2>

      <p>
        This lesson introduces the relationship between real-world events and
        the records created from them.
      </p>
    </div>

    <div class="lesson-overview-grid">

      <article class="lesson-overview-card">
        <span class="overview-card-label">Understand</span>

        <h3>What data represents</h3>

        <p>
          Explain why data is recorded information about reality rather than
          reality itself.
        </p>
      </article>

      <article class="lesson-overview-card">
        <span class="overview-card-label">Recognize</span>

        <h3>How data is created</h3>

        <p>
          Identify the choices, measurements, systems, and recording methods
          involved in producing a dataset.
        </p>
      </article>

      <article class="lesson-overview-card">
        <span class="overview-card-label">Build</span>

        <h3>Your first structured dataset</h3>

        <p>
          Transform an ordinary real-world event into a small table of
          variables and recorded values.
        </p>
      </article>

      <article class="lesson-overview-card">
        <span class="overview-card-label">Question</span>

        <h3>What the data leaves out</h3>

        <p>
          Examine missing context, possible inaccuracies, and the limits of
          recorded information.
        </p>
      </article>

    </div>

  </div>
</section>
  <section class="lesson-section">
    <div class="lesson-container lesson-content">

      <div class="lesson-heading">
        <span class="lesson-label">Learn</span>
        <h2>Data is recorded representation</h2>
      </div>

      <p>
        Something happens in the real world. A person visits a clinic, a
        machine records a temperature, a customer purchases a product, or a
        sensor detects motion. When information about that event is recorded,
        it becomes data.
      </p>

      <p>
        The record may be a number, word, image, sound, date, category,
        location, signal, or document. The form can change, but the central
        idea remains the same: data is information captured about something.
      </p>

      <div class="concept-box">
        <h3>Core idea</h3>

        <p>
          Data is a representation of reality created through observation,
          measurement, classification, or recording.
        </p>
      </div>

      <p>
        Because data is a representation, it is always incomplete. A row in a
        spreadsheet may represent a person, but it does not contain the full
        person. A medical image may represent anatomy and biological activity,
        but it does not contain every fact about the patient.
      </p>

    </div>
  </section>

  <section class="lesson-section lesson-section-alt">
    <div class="lesson-container">

      <div class="lesson-heading">
        <span class="lesson-label">Examples</span>
        <h2>One reality can produce many kinds of data</h2>

        <p>
          The same real-world event can be represented differently depending
          on what is observed and how it is recorded.
        </p>
      </div>

      <div class="example-grid">

        <article class="example-card">
          <h3>Healthcare</h3>

          <p>
            A patient visit may produce age, symptoms, diagnosis codes,
            laboratory values, imaging studies, medications, and clinical
            notes.
          </p>
        </article>

        <article class="example-card">
          <h3>Business</h3>

          <p>
            A purchase may produce product name, quantity, price, store,
            timestamp, payment method, and customer account information.
          </p>
        </article>

        <article class="example-card">
          <h3>Transportation</h3>

          <p>
            A trip may produce origin, destination, speed, travel time,
            distance, fuel use, traffic conditions, and route information.
          </p>
        </article>

      </div>

    </div>
  </section>

  <section class="lesson-section">
    <div class="lesson-container lesson-content">

      <div class="lesson-heading">
        <span class="lesson-label">From reality to dataset</span>
        <h2>How data is created</h2>
      </div>

      <div class="process-list">

        <article class="process-item">
          <div class="process-number">1</div>

          <div>
            <h3>An event or condition exists</h3>
            <p>
              Something occurs, changes, or is present in the real world.
            </p>
          </div>
        </article>

        <article class="process-item">
          <div class="process-number">2</div>

          <div>
            <h3>Someone decides what matters</h3>
            <p>
              A person or system selects which characteristics should be
              observed or measured.
            </p>
          </div>
        </article>

        <article class="process-item">
          <div class="process-number">3</div>

          <div>
            <h3>A method records the observation</h3>
            <p>
              The information may be entered manually, measured by an
              instrument, generated by software, or collected by a sensor.
            </p>
          </div>
        </article>

        <article class="process-item">
          <div class="process-number">4</div>

          <div>
            <h3>The record becomes part of a dataset</h3>
            <p>
              Individual observations are organized so they can be reviewed,
              compared, analyzed, and communicated.
            </p>
          </div>
        </article>

      </div>

    </div>
  </section>

  <section class="lesson-section lesson-section-alt">
    <div class="lesson-container lesson-content">

      <div class="lesson-heading">
        <span class="lesson-label">Important distinction</span>
        <h2>Data is not automatically truth</h2>
      </div>

      <p>
        Data can be useful evidence, but recording something does not guarantee
        that it is complete, accurate, unbiased, or properly understood.
      </p>

      <p>
        Measurements can be wrong. Categories can be poorly defined. Records
        can be missing. Sensors can fail. People can enter incorrect values.
        Important context may never be captured.
      </p>

      <div class="concept-box">
        <h3>Responsible interpretation</h3>

        <p>
          A data scientist should ask not only, “What does this dataset say?”
          but also, “How was it created, what does it leave out, and how much
          confidence should we place in it?”
        </p>
      </div>

    </div>
  </section>

  <section class="lesson-section">
    <div class="lesson-container">

      <div class="practice-box">
        <h2>Practice: Identify the representation</h2>

        <p>
          Choose one ordinary event, such as a medical visit, grocery purchase,
          work shift, school class, or car trip. Then answer:
        </p>

        <ol>
          <li>What happened in reality?</li>
          <li>What information could be recorded?</li>
          <li>Which variables would appear in the dataset?</li>
          <li>What important details might not be recorded?</li>
          <li>How could the record be inaccurate or misunderstood?</li>
        </ol>
      </div>

    </div>
  </section>
   <span class="lesson-label">Build</span>

<h2>Create your first dataset</h2>
  <section class="lesson-section lesson-section-alt">
    <div class="lesson-container lesson-content">

      <div class="lesson-heading">
        <span class="lesson-label">Reflect</span>
        <h2>Questions to deepen your understanding</h2>
      </div>

      <ul class="reflection-list">
        <li>
          Can two datasets describe the same event differently and both still
          be useful?
        </li>

        <li>
          Who decides what gets measured and what remains invisible?
        </li>

        <li>
          What is lost when a complex human experience is reduced to a number
          or category?
        </li>

        <li>
          How could incomplete data lead to a confident but incorrect
          conclusion?
        </li>
      </ul>

    </div>
  </section>

  <section class="lesson-section">
    <div class="lesson-container lesson-content">

      <div class="lesson-heading">
        <span class="lesson-label">Apply</span>
        <h2>Why this matters in real work</h2>
      </div>

      <p>
        In healthcare, business, research, government, and engineering,
        decisions are often made from recorded information. Good analysis
        therefore begins before statistics or programming. It begins by
        understanding what the data represents and how faithfully it reflects
        the real situation.
      </p>

      <p>
        This lesson forms the foundation for everything that follows. Before
        cleaning, visualizing, modeling, or predicting, we must understand the
        relationship between reality and the records created from it.
      </p>

      <div class="lesson-navigation">

        <a
          class="lesson-button lesson-button-secondary"
          href="{{ '/learn/data-science/level-1/' | relative_url }}">
          ← Return to Level 1
        </a>

        <a
  class="lesson-button"
  href="{{ '/learn/data-science/level-1/module-2/' | relative_url }}">
  Next: Types and Structures of Data →
</a>

      </div>

    </div>
  </section>

</main>