》》》JagritiSachdeva

CHAPTER 1

Big Data as “Big data is high-volume, high-velocity and/or high-variety information that demands cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

Introduction to Big Data

1. Big Data refers to extremely large datasets that are too complex and massive for traditional data-processing software to handle effectively.
2. These datasets come from a variety of sources, such as social media platforms, sensor networks, online transactions, and scientific research, and are characterized by their volume, velocity, variety, and more.
3. The ability to analyse and process Big Data enables businesses, governments, and organizations to gain valuable insights, make informed decisions, and drive innovation.

Characteristics of Big Data | 5V’s

The 5 Vs of Big Data are:

1. Volume – The massive amount of data generated every second.
   • Example: Social media platforms generate petabytes of data daily.
2. Velocity – The speed at which data is generated and processed.
   • Example: Stock market transactions happen in real-time.
3. Variety – Different types of data (structured, semi-structured, unstructured).
   • Example: Text, images, videos, and sensor data from IoT devices.
4. Veracity – The reliability and accuracy of data.
   • Example: Filtering fake news from real news in social media analytics.
5. Value – The usefulness of data in decision-making.
   • Example: Retail businesses using customer purchase history for personalized recommendations.

Importance of Big Data

1. Improved Decision-Making – Data-driven insights help businesses and organizations make informed decisions.
   • Example: Companies use customer behavior data to refine marketing strategies.
2. Enhanced Efficiency – Automates processes and optimizes operations.
   • Example: Predictive maintenance in manufacturing reduces downtime.
3. Better Customer Experience – Personalizes services based on user data.
   • Example: Streaming services like Netflix recommend shows based on watch history.
4. Fraud Detection & Security – Identifies anomalies and prevents cyber threats.
   • Example: Banks use AI to detect fraudulent transactions in real-time.
5. Scientific & Healthcare Advancements – Supports research and innovation.
   • Example: Genomic data analysis helps in personalized medicine and disease prediction.