Big data : Coudbells.com
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This document introduces big data by defining it as large, diverse data that requires new techniques to extract value from. It notes that big data comes from many sources like sensors, social media, purchases, and cell phones. Big data is characterized by its scale (volume), complexity (variety), and speed (velocity). It provides examples of how big data is used for personalized promotions and healthcare monitoring. Finally, it outlines how much data companies like Google, Facebook, and eBay process daily and yearly, demonstrating how big data is everywhere and can increase productivity and sales.
Big data : Coudbells.com
- 1. INTRODUCTION TO BIG DATA
- 2. $ What is Big Data? What makes data, “Big” Data?
- 3. DEFINATION “Big Data” is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it… This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.
- 4. Characteristics of Big Data Scale (Volume) Data Volume 44x increase from 2009 2020 From 0.8 zettabytes to 35zb Data volume is increasing exponentially
- 5. Complexity (Variety) •Various formats, types, and structures •Text, numerical, images, audio, video, sequences, time series, social media data, multi-dim arrays, etc… •Static data vs. streaming data •A single application can be generating/collecting many types of data
- 6. Speed (Velocity) •Data is begin generated fast and need to be processed fast •Online Data Analytics •Late decisions missing opportunities •EXAMPLES E-Promotions: Based on your current location, your purchase history, what you like send promotions right now for store next to you Healthcare monitoring: sensors monitoring your activities and body any abnormal measurements require immediate reaction
- 8. Some Makes It 4 V’s
- 9. Big Data Is Everywhere Lots of data is being collected and warehoused •Web data, e-commerce •Purchases at department/grocery stores •Bank/Credit Card transactions •Social Network
- 10. How much data? • Google processes 20 PB a day (2008) • Wayback Machine has 3 PB + 100 TB/month (3/2009) • Facebook has 2.5 PB of user data + 15 TB/day (4/2009) • eBay has 6.5 PB of user data + 50 TB/day (5/2009) • CERN’s Large Hydron Collider (LHC) generates 15 PB a year 640K ought to be enough for anybody.
- 11. Increase in Productivity & Sales
- 12. Thank You