ملخص: Big Data

Learning Objectives

• Explain the characteristics of big data.
• Discuss secure sources of big data.
• Infer the types of big data.

The Concept of Big Data

Big data is a collection of large, complex data that cannot be processed efficiently with traditional technology such as Excel. Analyzing it helps analysts, researchers and entrepreneurs make better and faster decisions.

Sources of Big Data

1. Internet-connected devices (IoT): smart refrigerators, smart watches and connected cars constantly produce data about location, temperature, behavior and energy use. A smart watch measures heart rate, activity level and temperature and sends them to an app.
2. Social media: posts, comments, photos, videos and likes create data about time, location, reactions and hashtags (these sources may be unreliable).
3. Financial data: electronic payments, banking and stock trading record amounts, users, places and times.
4. Smart devices: phones, cameras and smart-home devices produce data about usage, location and interactions.
5. Digital content: videos, images and audio generate views, interactions, comments and shares.
6. Government data: population registers, statistics, tax data and censuses.
7. Geographic and spatial data: satellites and GPS devices collect data about locations, roads and the environment; a mapping app uses traffic and vehicle speed to improve routing.

The 5 Vs of Big Data

Types of Big Data

• Structured data: organized in tables with rows and columns, like traditional databases. Examples: customer data, financial data, transaction records.
• Unstructured data: not in a table or database form and hard to analyze with traditional tools. Sources: text, images, videos and social media posts, for example a Facebook post with text, images and video.
• Semi-structured data: a mix of both. Emails are a good example: the message body is unstructured, while sender, recipient, subject and date give structure.

Why Big Data Matters

Analyzing big data allows analysts, researchers and entrepreneurs to make better and faster decisions, because traditional tools such as Excel cannot process it efficiently. Examples of its use: a mapping app such as Google Maps uses traffic and vehicle-speed data to improve routing, and a smart watch sends health data to its app. Extracting real value depends on the reliability and quality of the data (veracity).

Using Data Responsibly

Always record data accurately and cite the sources you rely on. This increases the reliability of information and helps verify its accuracy.