Big Data

Big Data

1. Origins:

   • It emerges with the exponential growth of digital data.
   • Associated with the rise of the Internet, social media, mobile devices, and sensors.
   • The term began to be used in the late 1990s.
   • Evolution of massive storage and processing technologies.

2. Main definitions of Big Data

   • IBM defines it through the "3 Vs": Volume, Velocity, and Variety.
   • Includes both structured and unstructured data.
   • A data set so large, fast, or complex that it exceeds the capabilities of traditional processing tools.

3. Implications of Big Data

   • Changes in data-driven decision-making.
   • New opportunities in areas such as healthcare, finance, marketing, and government.
   • Ethical challenges related to privacy and the use of information.
   • Digital transformation of organizations.

4. Motivations for using Big Data

   • Gain competitive advantages through predictive analytics.
   • Optimize processes and reduce costs.
   • Better understand customers and personalize products or services.
   • Detect patterns, fraud, or anomalous behavior.