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  1. Big Data: Electronic Gold And why Oreus should invest in Big Data Thomas Snuverink

  2. Big Data is everything Limitless possibilities: • Doctor Movement • Social Media connections • Purchase Behavior • Weather Predictions Big Data is “the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications” The 3V’s: • Velocity • Variation • Volume Big Data is not necessarily big: • Traffic data in Waze • Product movement within factory • Ford Fusion data processor

  3. Big Data is everywhere Government Science Commercial • NSA: going through your emails, Skype conversations and Facebook messages • Rijkswaterstaat improvement of flood control • Realtime data collection and analysis at LHC CERN • DNA Genomics analysis • SETI project looking for alien life • Walmart product placement • AlberHeijnBonuskaart • Facebook, Twitter and LinkedIn User Data

  4. Big Data is getting big due to hardware and software innovation, and The Internet of Things Hardware Innovations • Larger Data Storage Facilities • Faster Supercomputers Software Innovations • Introduction of Hadoop and NoSQL • Improvement in Visualization Tools • The Internet of Things: We create and capture more data about ourselves • RFID • GPS • Mobile Devices/Connectivity (WiFi/3G/4G) • Cameras • Sensors • Social Media: Moods and Emotions

  5. Big Data is monetized in 3 ways It makes companies more efficient It is a company’s key product It is a company’s key differentiator • UPS efficient fleet management • Savings: $20 million a year on fuel alone • Increasing Seattle Children’s Hospital efficiency by basing layout on big data • Savings: $23 million a year • Companies offering their Big Data capabilities: • IBM • SAP • Oracle • User information for advertisement: • Facebook • Twitter • Google • Netflix and ‘s recommender systems • Banks using Big Data for predictions, analysis and product creation

  6. The Big Data market will grow enormously Big Data 2012* • $813 Million • Main players: • IBM (18.6%) • Intel (14.9%) • HP (10%) • Fujitsu (5.6%) • Main segments: • Storage (15%) • Services (38%) • Analytics (20%) Big Data 2016* • $51 Billion* • $16 Billion in revenue for IBM alone • Data storage segment will grow most (53%) • Healthcare is the fastest growing target market *IDC predictions

  7. Big Data is BIG MONEY Peter Sondergaard (Gartner): “By 2020, every company will be an IT company and every leader will be a digital leader.” McKinsey GI: “The effective use of Big Data has the potential to transform economies, delivering a new wave of productivity growth and consumer surplus.” Chief Digital Strategist Obama: “Big Data is about what your relationship is with the people who are most important to you and an awareness of the potential in that relationship.”

  8. There is a wide range of Big Data companies both establishes and start-up Established • IBM: First-mover in Big Data that offers both hard and software • Intel: Leverages its competence in chip-building to provide top of the line Big Data hardware. • Combines its two core competences of cloud-based services and handling large amounts of data as a cloud SaaS to clients. Start-ups • DataSift: software to analyze social media data. • Karmasphere: software to analyze large amounts of data generated in collaborative projects. • Retention Science: software to analyze customer data and reduce churn. Focused primarily on software and many more than these examples. All of which are hugely successful and are currently raising venture capital. Focused primarily on large clients and total Big Data packages often including the hardware needed for Big Data analysis.

  9. Oreus can profit from the Big Data surge by investing in Big Data Start-ups • Large players are too diversified to profit from the Big Data surge as • Small start-ups are more flexible and attentive to niches and new applications of Big Data • Software of start-ups focus enables low investments • Dutch Big Data Start-Ups: • Synerscope: building software to visualize big data inferences • Algoritmica: software modelling for predective uses • Dataquote: customer analysis for the real-estate market