Unit 2: Data Literacy

Empowering Students to Understand, Use, and Analyze Data

1. What is Data Literacy?

Data Literacy is the ability to derive meaningful information from data. Just as reading and writing are essential skills, understanding data is the new "literacy" in the age of AI.

The Core Concept: Data is the "raw material." Data Literacy is the "skill" used to process that material into useful "insights."

2. Types of Data: Structured vs Unstructured

Machines process different types of data in different ways:

Structured Data: Highly organized and easy to search (e.g., Excel sheets, SQL databases).
Unstructured Data: Has no pre-defined format (e.g., Photos, Audio files, Social media posts). This is where AI (Computer Vision and NLP) is most useful!

3. The Data Lifecycle

Data goes through several stages before an AI can use it effectively:

1. Data
Acquisition

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2. Data
Cleaning

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3. Data
Analysis

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4. Data
Visualization

4. Data Ethics & Bias

If the data used to train an AI is biased (incorrect or unfair), the AI's decisions will also be biased. This is often called GIGO: Garbage In, Garbage Out.

🕵️ Live Activity: The Data Detective

How much data does the world generate in a single minute? Explore "Data Never Sleeps" to see the massive scale of modern data acquisition.

View Live Data Scale 📊

Task: Identify three sources of "Unstructured Data" mentioned in the infographic.

Continue learning

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AI Logic School

Class 9 AI | Unit 2 : Data Literacy – Understanding the Fuel of AI