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  2. AP Computer Science Principles
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Extracting Information from Data

Chloe Evans

Chloe Evans

7 min read

Next Topic - Using Programs with Data

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Study Guide Overview

This study guide covers data and big data, including transforming data into information, the rise of big data, server farms and data centers, and scalability. It also explores metadata, its uses, and challenges in data collection and processing, such as data uniformity and cleaning data. Finally, it addresses data biases, understanding and mitigating them. Key terms include correlation vs. causation, and the guide provides practice questions and exam tips.

#AP Computer Science Principles: Data & Big Data - Your Night-Before Guide 🚀

Hey there! Feeling the pressure? Don't worry, we've got you covered. This guide is designed to be your super-efficient, last-minute review for the AP Computer Science Principles exam. Let's get started!

#1. The Power of Data & Big Data

#1.1. Transforming Data into Information

  • Data becomes information when we analyze it to find trends, connections, and solutions.
  • Think of data as raw ingredients and information as the delicious meal you make with them.
Key Concept

Larger data sets (Big Data) help establish more reliable patterns and conclusions than smaller ones.

- **Correlation ≠ Causation**: Just because two things happen together doesn't mean one causes the other. 💡

#1.2. The Rise of Big Data

  • The world is increasingly interconnected, leading to massive amounts of data.
  • Example: Global shipping data (Shipmap) demonstrates the scale of data being tracked.
  • Computers are essential for processing big data due to their speed and accuracy.
Quick Fact

Parallel systems and multiple computers are often needed for large-scale data processing.

#1.3. Server Farms & Data Centers

  • Server farms house many computers to meet intense processing needs.
  • They are often located in large data centers.
Memory Aid

Think of data centers as giant libraries, but instead of books, they store and process information.

#1.4. Scalability

  • Scalability is a system's ability to adapt to increasing or decreasing data loads.
  • A scalable system can handle more data without fundamentally changing its operation.
Exam Tip

Scalability is crucial for efficient big data processing.

Practice Question

Multiple Choice:

  1. Which of the following best describes the relationship between data and information? (A) Data is processed to become information. (B) Information is raw and unprocessed, while data is refined. ...
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Question 1 of 13

🎉 What happens when we analyze data to find trends and connections?

It becomes raw data

It becomes information

It is deleted

It stays as data