What are the main sources of big data, and how does aggregation of small datasets create privacy risks?

Big data is often built by aggregating many small, seemingly harmless datasets from digital platforms, location services, communications, and IoT devices.

Key sources of big data:

• Digital platforms: Web data, e-commerce, mobile phone data.
• Location data: Cell tower triangulation, GPS, movement profiles, location history.
• Communication and social networks: Emails, Facebook, LinkedIn, Twitter, and others.
• Internet of Things: Health sensors, quantified-self devices, smart home systems.

The aggregation problem: Big data is frequently created by combining small datasets from a very large number of sources. Each individual piece might seem harmless. But combined, they create a detailed portrait.

The Swisscom "Ville Vivante" project proved this: just cell tower connection logs, not even call content, revealed the movement patterns of an entire city. 15 million "movements" were measurable from 2 million phone calls in a single day in Geneva.

Why this matters for privacy: Traditional data protection was designed for a world where data collection was limited and expensive. Big data flips this on its head, collecting as much as possible because storage is cheap, and finding uses for it later.