By Michael Minelli
Chapter 1 what's large information and Why Is It vital? (pages 1–18):
Chapter 2 Examples of massive facts (pages 19–59):
Chapter three titanic information expertise (pages 61–88):
Chapter four info administration (pages 89–98):
Chapter five enterprise Analytics (pages 99–125):
Chapter 6 the folk a part of the Equation (pages 127–149):
Chapter 7 facts privateness and Ethics (pages 151–167):
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Additional info for Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses
The barriers to enter the affiliate marketing industry as an affiliate no longer exist. Above and beyond the removal of barriers the social web brings to affiliate marketing, it also brings into the mix the same concepts behind the Avon Lady and Tupperware party—product recommendations from a friend INDUSTRY EXAMPLES OF BIG DATA 31 network. As many detailed studies have shown, most people trust a recommendation from the people they know. While professional affiliate marketing sites provide the aggregation of many merchant offers on one centralized site, they completely lack the concept of trusted source recommendations.
The Capgemini Financial Services team believes that due to the nature of data streams and processing required, Big Data technologies provide an optimal technology solution based on the following three Vs: 1. High volume. Years of customer records and transactions (150 billion1 records per year) 2. High velocity. Dynamic transactions and social media information 3. High variety. Social media plus other unstructured data such as customer emails, call center conversations, as well as transactional structured data Capgemini’s new fraud Big Data initiative focuses on flagging the suspicious credit card transactions to prevent fraud in near real-time via multi-attribute monitoring.
That’s the current state of unstructured data as of today. Tomorrow will be a different story because there’s a lot of money to be made for smart individuals and companies that can mine unstructured data successfully. The implosion of data is happening as we begin to embrace more open and transparent societies. “Résumés used to be considered private information,” says Ghosh. ” We have similar stories with Instagram and Flickr for pictures, Facebook for our circle of 12 BIG DATA, BIG ANALYTICS friends, and Twitter for our personal thoughts (and what the penalty can be given the recent London Olympics, where a Greek athlete was sent home for violating strict guidelines on what athletes can say in social media).