Data Science Grade IX - Notes

Introduction to Data

Data is facts or information used for decision making, calculation, or discussion. It can be numbers, alphabets, symbols, or a combination of these. Various sensors, machines and apps generate massive amounts of data daily.

Data vs. Information

Data alone has no meaning. When data is processed, organized, and analyzed, it becomes information, providing context and meaning. For example, a list of temperatures becomes information when it shows a trend of rising global temperatures.

DIKW Model

The DIKW (Data, Information, Knowledge, Wisdom) model explains the transformation of data into information, then into knowledge, and finally into wisdom. For example, 100°C100°C (data) is the boiling point of water (information), which leads to the knowledge that touching boiling water can cause burns (wisdom).

Influence of Data

Data and its analysis significantly impact various aspects of life:

  • Healthcare: Tracking medical history, predicting disease transmission.
  • Online Shopping: Targeted marketing based on purchase history.
  • Education: Digitized admission processes and career options analysis.
  • Travel: Predicting traffic and analyzing traveler feedback.
  • Online Shows: Personalized content recommendations based on watch history.

Data Footprints

Data footprints are trails of data created through internet activities. They are classified into:

  • Active: Knowingly shared information on social media.
  • Passive: Browsing history and product searches stored for personalized marketing.

Data Loss and Recovery

Data loss can occur due to system crashes or disk failures. Data recovery is the process of restoring lost, corrupted, or deleted data. Regular data backups are essential to prevent data loss.

Activity: Ladybugs

An activity is described involving collecting and summarizing data on ladybugs, including the number of spots and color. Numerical variables (quantitative variables) and categorical variables are considered.