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Big Data: Opportunity & Challenges

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IEEE Lecture for UIN Syarif Hidayatullah, Jakarta 2014.

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Big Data: Opportunity & Challenges

  1. 1. Kuncoro Wastuwibowo Chair, IEEE Indonesia Section Jakarta, 15 October 2014
  2. 2. IEEE is the world's largest professional association dedicated to advancing technological innovation and excellence for the benefit of humanity. IEEE and its members inspire a global community through IEEE's highly cited publications, conferences, technology standards, and professional and educational activities.
  3. 3. IEEE has  more than 425,000 members in more than 160 countries;  more than 116,000 Student members;  333 Sections in 10 geographic regions worldwide;  2,195 Chapters that unite local members with similar technical interests;  2,354 student branches at colleges and universities;  800 student branch chapters of IEEE technical societies; IEEE  has 38 Societies and 7 technical Councils representing the wide range of IEEE technical interests;  has more than 3 million documents in the IEEE Xplore Digital Library, with more than 8 million downloads each month;  has more than 1,400 standards and projects under development;  publishes more than 148 transactions, journals, and magazines;  sponsors more than 1,300 conferences in 80 countries while:  publishing more than 1,200 conference proceedings via IEEE Xplore.
  4. 4. Board ofDirectors MEMBERS Educational Activities Board Professional Activities Board Publications Activities Board Regional Activities Board Standards Activities Board Technical Activities Board MEMBERS Board of Directors Assembly PSPB IEEE-USA Standards Assoc.EAB MGA TAB Executive Comm. Regions & Sections Societies & Councils Staff & Society Exec. Directors Chapters
  5. 5. Internet 2.0 Internet 3.0 Total Experience Services Context-aware Applications Internet of Things Big Data & Analytics Smart Applications Wisdom of Crowds Mash-up Applications User-Generated Content
  6. 6. “Business Intelligence ” Data Discovery Things We Know Things We Don’t Know Questions We Ask Questions We Don’t Ask
  7. 7. Science & Technology• Search for Extra- Terrestrial Intelligence (SETI) • Genome projects • CERN’s Large Hadron Collider • The Square Kilometer Telescope Array • Social Genome Business & Community• Consolidation of government data holdings • Consumer profile databases • Customer relationship management • Social Media • Sensor data
  8. 8. Sensing Data Cyberspace Physical Space Actionable Information Ubiquitous Internet
  9. 9. Device Provider 3rd Party Context Enabler Context Provider Service Platform Provider Content Provider User Network Provider Service Provider Platform Provider Context Platform Context Data Context Data Context Data Context Context-Aware Services
  10. 10. Google Search •User’s interest •User’s behaviour Google Mail •User’s profile •User’s behaviour & schedule •User’s relation •(Even for Mac & iOS users) Google+ •User’s relation •User’s behaviour Google Maps •User’s location •User’s interest Youtube •User’s interest •User’s network capacity Chrome •User’s behaviour •User’s interest •(Even for Mac users) Android •User’s device •User’s location •User’s behaviour •User’s application usage Google Docs •User’s business •User’s schedule Google Translate •User’s business •User’s interest Google Playstore •Guess it! Google Scholar •Guess it! Google Drive •Guess it!
  11. 11. Google • Google Search • Google Now • Google Glass Apple • Siri • Apple Watch • iPhoto (autometically managed with time, location, event) • Health
  12. 12. Target customers by capturing useful information about them Identify more effective product promotions and create offers targeted to specific customers. Predict the risk of each customer going to other companies and then identify actions likely to keep them loyal. Improve efficiency by reducing unused capacity or unnecessary duplication WHY? Organizations leveraging analytics will have a greater competitive advantage. Those that don’t will lag behind their peers.
  13. 13. Big data analytics is valuable to many companies but has been too complex and expensive for smaller businesses. This is beginning to change.
  14. 14. Suvola • Integrated systems using hardware and software from selected vendors to allow smaller organizations buy simpler, more affordable all-in- one systems for which the seller provides maintenance and support. Big Vendors • IBM • Oracle • SAP • SAS Start-ups • QlickTech • Tableau Software • Tidemark
  15. 15. Uptime Sotware Continuui ty Right Scale Amazo n Cloudy n Cloud Vertical Newvem BigML Insights One Splunk Storm Rack space Cloudabilit y
  16. 16. The Internet will enhance global connectivity, fostering more planetary relationships and less ignorance. The IoT, artificial intelligence, and big data will provide more awareness of the world and our own behavior. Augmented reality and wearable devices will monitor and give quick feedback on daily life (for example, to enhance personal health). Political awareness and action will be facilitated. More peaceful change and public uprisings will emerge. Internet will diminish the meaning of borders, and new “nations” of those with shared interests may emerge.
  17. 17.  Dangerous divides between haves and have-nots may expand, resulting in resentment and possible violence.  Abuses and abusers will “evolve and scale.” Human nature isn’t changing; laziness, bullying, stalking, stupidity, pornography, dirty tricks, and crime will continue, and those who practice them have new capacity to make life miserable for others.  Pressured by these changes, governments and corporations will try to assert power—and at times succeed—as they invoke security and cultural norms.  People will continue—sometimes grudgingly—to make tradeoffs, favoring convenience and perceived immediate gains over privacy. Privacy will become something only the upscale enjoy.  Humans and their current organizations may not respond quickly enough to challenges presented by complex networks.  Most people haven’t yet noticed the profound changes today’s communications networks are already bringing about; these networks will be even more disruptive in the future.
  18. 18. Encryption isn’t a perfect solution for securing big data, but it could be a valuable component in a comprehensive privacy solution. Third parties would create various privacy profiles for consumers who would then select a profile such that data holders would be required to differentiate the way they use data based on each consumer’s selection. Anonymisation and de-identification have limited relevance because data points linked to one another tend to take on other identifiable attributes. Deletion and non-retention policies aren’t effective means of protecting individual privacy.
  19. 19. The focus should be on the actual uses of big data and not so much on its collection and analysis. To avoid obsolescence, policies and regulations should be stated in terms of intended outcomes and not embed particular technological solutions. The Government should strengthen its research in privacy- related technologies. There should be more education and training opportunities concerning privacy protection. The Government should take the lead by adopting policies that stimulate the use of practical privacy-protecting technologies that exist today.
  20. 20. Kuncoro Wastuwibowo Chair IEEE Indonesia Section info@IEEE.web.id http://IEEE.web.id @IEEEIndonesia
  21. 21. IEEE Indonesia Section info@IEEE.web.id http://IEEE.web.id @IEEEIndonesia
  22. 22.  Brian M. Gaff, Heather Egan Sussman, Jennifer Geetter, Privacy and Big Data, IEEE Computer, June 2014  George F. Hurlburt, Jeffrey Voas, Big Data, Networked Worlds, IEEE Computer, April 2014  Jason Kolb & Jeremy Kolb, The Big Data Revolution, Applied Data Labs Inc 2013.  Neal Leavitt, Bringing Big Analytics to the Masses, IEEE Computer, January 2013  Niklas Elmqvist & Pourang Irani, Ubiquitous Analytics: Interacting with Big Data Anywhere, Anytime, IEEE Computer, April 2013  Pew Research Center, Digital Life in 2025, March 2014  President’s Council of Advisors on Science and Technology, Report to the President: Big Data and Privacy – A Technological Perspective, May 2014.  Xiaomeng Yi, Fangming Liu, Jiangchuan Liu, and Hai Jin, Building a Network Highway for Big Data: Architecture and Challenges, IEEE Network, July/August 2014  Yin Zhang, Min Chen, Shiwen Mao, Long Hu, and Victor C. M. Leung, CAP: Community Activity Prediction Based on Big Data Analysis,