Big Data, Cloud, Smart Mobile And Even AR Morph Into One Mind Boggling Thing

IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: Actually One Big Thing

by David Mayes

This IEEE Talk discusses the three biggest trends in online technology and proposes that in fact, they represent one huge integrated trend that is already having a major impact on the way we live, work and think. The 2012 Obama Campaign’s Dashboard mobile application, integrating Big Data, The Cloud, and Smart Mobile is perhaps the most significant example of this trend, combining all three technologies into one big thing. A major shakeout and industry consolidation seems inevitable. Additional developments as diverse as augmented reality, the Internet of Things, Smart Grid, near field communication, mobile payment processing, and location-based services are also considered as linked to this overall trend.

IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: Big Deal or Not? from David Mayes

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IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: Big Deal or Not? Presentation Transcript

• 1. Big Data, The Cloud, & Smart Mobile: Integrated Big Deal or Not? ©David Mayes 1
• 2. IEEE: UBC Okanagan Wednesday, February 6th, 2013 ©David Mayes 2
• 3. Speaker Introduction IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 3
• 4. David Mayes: LinkedIn Profile: http://www.linkedin.com/in/mayo615 Personal Blog: http://mayo615.com UBC Office: EME 4151 (250) 807-9821 / Hours by appt. Email: david.mayes@ubc.ca mayo0615@gmail.com Mobile: (250) 864-9552 Twitter: @mayo615 Experience: Executive management, access to venture capital, International business development, sales & marketing, entrepreneurial mentorship, technology assessment, strategic planning, renewable energy technology. Intel Corporation (US/Europe/Japan), 01 Computers Group (UK) Ltd, Mobile Data International (Canada/Intl.), Silicon Graphics (US), Sun Microsystems (US), Ascend Communications (US/Intl.), P-Cube (US/Israel/Intl.), Global Internet Group LLP (US/Intl.), New Zealand Trade & Enterprise. IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 4
• 5. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 5
• 6. Some Historical Context IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 6
• 7. Canada’s McLuhan: The First Hint “The new electronic interdependence recreates the world in the image of a global village.” Marshall McLuhan, “Gutenberg Galaxy”, 1962, Canadian author, educator, & philosopher (1911 – 1980) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? Video: The “McLuhan” Scene from Annie Hall © David Mayes 7
• 8. Stuart Brand, Jobs & Woz: The Whole Earth Catalog IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 8
• 9. Grove, Noyce and Moore IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? “We had no idea at all that we had turned the first stone on something that was going to be an $80 billion business.” -Gordon Moore ©David Mayes 9
• 10. Sir Tim Berners-Lee and Vin Cerf IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 10
• 11. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 12. The Emergence of SoMoClo IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? Social + Mobile + Cloud ©David Mayes 12
• 13. Emergence of Social Media IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 13
• 14. 2012 Social Media Market Landscape IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 14
• 15. Emergence of “Cloud Computing” IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 15
• 16. Emergence of End-user Cloud Apps IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 16
• 17. 2012 Cloud Enterprise Players IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 17
• 18. The Key Issue: Data Privacy Reliability, and Security Despite reassurances, there is no permanent solution, no silver bullet. The only solution is to unplug IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 18
• 19. Recent Cyber Security News: • Google Chairman, Eric Schmidt’s new book on China: • “the world’s most active and enthusiastic filterer of information” as well as “the most sophisticated and prolific” hacker of foreign companies. In a world that is becoming increasingly digital, the willingness of China’s government and state companies to use cyber crime gives the country an economic and political edge. • NY Times, WSJ hacking last week traced to China • Twitter theft of 250K users personal information last week • Sony PlayStation Anonymous hacks (twice in 2 weeks) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 19
• 20. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 21. The Emergence of “Big Data” IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 21
• 22. Emergence of “Big Data” • Major advances in scale and sophistication of government intelligence gathering and analysis • Cost no object • NSA PRISM global telecom surveillance programPost 9/11 World IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 22
• 23. An Interesting Scientific Analogy Chaos, with reference to chaos theory, refers to an apparent lack of order in a system that nevertheless obeys particular laws or rules; this understanding of chaos is synonymous with dynamical instability, a condition discovered by the physicist Henri Poincare in the early 20th century that refers to an inherent lack of predictability in some physical systems. IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 23
• 24. Key Drivers of the Emergence of Big Data • Moore’s Law – compute cost and power • Design rules, multi-core, 3D design • Massive cost decline in data storage • Emergence of solid state memristor • Google Spanner 1st global real-time database • DARPA “Python” programming language • Data Center data storage accumulation • 2.7 zettabytes currently and growing rapidly • A zettabyte equals 1021 bytes (1000 exabytes) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 24
• 25. The Big Data Landscape Today IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 25
• 26. The Key Issue: Privacy “Get over it! You have no privacy!” Scott McNealy, former CEO of Sun Microsystems IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 26
• 27. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 28. The Emergence of Smart Mobile IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 28
• 29. Emergence of Smart Mobile IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 29
• 30. Key Drivers of Smart Mobile • Moore’s Law – compute cost and power • Design rules, multi-core, 3D design • Focus on reducing heat: gate leakage • Intel Atom “all day battery life” is a beginning • Massive cost decline in data storage • Mobile bandwidth:4G/LTE “no cost difference” • “White space” metro Wi-Fi potential maybe • New available spectrum between digital TV channels: increased transmit power • PC market death: Dell Computer & HP IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 30
• 31. Mobile-based Services • GPS, Cloud, personal and database info on mobile • Geotagging from current location tied to your objective: • Find merchandise, restaurant, bar, etc. • Find and tag people • Find people with similar interests nearby • The rise of the mobile gaming market • Already well-established in Hong Kong, Seoul • North America far behind Asian telecom markets • Facebook has just announced LBS plans • The downside: battery drain issue still critical • “People want their phones to do too much” • 4G LTE, Wifi, Bluetooth, GPS, Streaming, Mobile Gaming IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 31
• 32. Location-based Services Landscape IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 32
• 33. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 34. The Convergence of “ToDaClo” Touch + Data + Cloud IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 34
• 35. David Mayes ‹#›
• 36. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 37. Discussion: Big Data, The Cloud, and Smart Mobile, Big Deal or Not? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 37
• 38. My Key Takeaway Points • Even from the 50,000 foot level, a shakeout and consolidation seem inevitable • A lot of people are going to lose a lot of money • There will be “snake oil” sold that does not work • Nevertheless these three new markets are actually one unified market, and likely: The Next Big Thing IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 38
• 39. What Do You Think? • No. ToDaClo is mostly media hype, and not a “Big Deal.” • I’m skeptical. ToDaClo will probably be a “Big Deal,” but I haven’t seen much yet • Maybe. I do not know yet whether ToDaClo will be a Big Deal • Yes. ToDaClo is a Big Deal and it is already changing our lives IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 39
• 40. Thank You! IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 40
• 41. ©David Mayes 41

 

Integrated Big Data, Cloud, and Smart Mobile: One Big Deal or Not?

IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: One Big Deal or Not?

by David Mayes on Jul 10, 2013

This IEEE Talk discusses the three biggest trends in online technology and proposes that in fact, they represent one huge integrated trend that is already having a major impact on the way we live, work and think. The 2012 Obama Campaign’s Dashboard mobile application, integrating Big Data, The Cloud, and Smart Mobile is perhaps the most significant example of this trend, combining all three technologies into one big thing. A major shakeout and industry consolidation seems inevitable. Additional developments as diverse as the Internet of Things, Smart Grid, near field communication, mobile payment processing, and location based services are also considered as linked to this overall trend.

IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: Big Deal or Not? from David Mayes

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IEEE Talk: Integrated Big Data, The Cloud, & Smart Mobile: Big Deal or Not? Presentation Transcript

• 1. Big Data, The Cloud, & Smart Mobile: Integrated Big Deal or Not? ©David Mayes 1
• 2. IEEE: UBC Okanagan Wednesday, February 6th, 2013 ©David Mayes 2
• 3. Speaker Introduction IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 3
• 4. David Mayes: LinkedIn Profile: http://www.linkedin.com/in/mayo615 Personal Blog: http://mayo615.com UBC Office: EME 4151 (250) 807-9821 / Hours by appt. Email: david.mayes@ubc.ca mayo0615@gmail.com Mobile: (250) 864-9552 Twitter: @mayo615 Experience: Executive management, access to venture capital, International business development, sales & marketing, entrepreneurial mentorship, technology assessment, strategic planning, renewable energy technology. Intel Corporation (US/Europe/Japan), 01 Computers Group (UK) Ltd, Mobile Data International (Canada/Intl.), Silicon Graphics (US), Sun Microsystems (US), Ascend Communications (US/Intl.), P-Cube (US/Israel/Intl.), Global Internet Group LLP (US/Intl.), New Zealand Trade & Enterprise. IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 4
• 5. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 5
• 6. Some Historical Context IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 6
• 7. Canada’s McLuhan: The First Hint “The new electronic interdependence recreates the world in the image of a global village.” Marshall McLuhan, “Gutenberg Galaxy”, 1962, Canadian author, educator, & philosopher (1911 – 1980) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? Video: The “McLuhan” Scene from Annie Hall © David Mayes 7
• 8. Stuart Brand, Jobs & Woz: The Whole Earth Catalog IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 8
• 9. Grove, Noyce and Moore IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? “We had no idea at all that we had turned the first stone on something that was going to be an $80 billion business.” -Gordon Moore ©David Mayes 9
• 10. Sir Tim Berners-Lee and Vin Cerf IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 10
• 11. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 12. The Emergence of SoMoClo IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? Social + Mobile + Cloud ©David Mayes 12
• 13. Emergence of Social Media IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 13
• 14. 2012 Social Media Market Landscape IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 14
• 15. Emergence of “Cloud Computing” IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 15
• 16. Emergence of End-user Cloud Apps IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 16
• 17. 2012 Cloud Enterprise Players IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 17
• 18. The Key Issue: Data Privacy Reliability, and Security Despite reassurances, there is no permanent solution, no silver bullet. The only solution is to unplug IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 18
• 19. Recent Cyber Security News: • Google Chairman, Eric Schmidt’s new book on China: • “the world’s most active and enthusiastic filterer of information” as well as “the most sophisticated and prolific” hacker of foreign companies. In a world that is becoming increasingly digital, the willingness of China’s government and state companies to use cyber crime gives the country an economic and political edge. • NY Times, WSJ hacking last week traced to China • Twitter theft of 250K users personal information last week • Sony PlayStation Anonymous hacks (twice in 2 weeks) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 19
• 20. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 21. The Emergence of “Big Data” IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 21
• 22. Emergence of “Big Data” • Major advances in scale and sophistication of government intelligence gathering and analysis • Cost no object • NSA PRISM global telecom surveillance programPost 9/11 World IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 22
• 23. An Interesting Scientific Analogy Chaos, with reference to chaos theory, refers to an apparent lack of order in a system that nevertheless obeys particular laws or rules; this understanding of chaos is synonymous with dynamical instability, a condition discovered by the physicist Henri Poincare in the early 20th century that refers to an inherent lack of predictability in some physical systems. IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 23
• 24. Key Drivers of the Emergence of Big Data • Moore’s Law – compute cost and power • Design rules, multi-core, 3D design • Massive cost decline in data storage • Emergence of solid state memristor • Google Spanner 1st global real-time database • DARPA “Python” programming language • Data Center data storage accumulation • 2.7 zettabytes currently and growing rapidly • A zettabyte equals 1021 bytes (1000 exabytes) IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 24
• 25. The Big Data Landscape Today IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 25
• 26. The Key Issue: Privacy “Get over it! You have no privacy!” Scott McNealy, former CEO of Sun Microsystems IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 26
• 27. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 28. The Emergence of Smart Mobile IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 28
• 29. Emergence of Smart Mobile IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 29
• 30. Key Drivers of Smart Mobile • Moore’s Law – compute cost and power • Design rules, multi-core, 3D design • Focus on reducing heat: gate leakage • Intel Atom “all day battery life” is a beginning • Massive cost decline in data storage • Mobile bandwidth:4G/LTE “no cost difference” • “White space” metro Wi-Fi potential maybe • New available spectrum between digital TV channels: increased transmit power • PC market death: Dell Computer & HP IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 30
• 31. Mobile-based Services • GPS, Cloud, personal and database info on mobile • Geotagging from current location tied to your objective: • Find merchandise, restaurant, bar, etc. • Find and tag people • Find people with similar interests nearby • The rise of the mobile gaming market • Already well-established in Hong Kong, Seoul • North America far behind Asian telecom markets • Facebook has just announced LBS plans • The downside: battery drain issue still critical • “People want their phones to do too much” • 4G LTE, Wifi, Bluetooth, GPS, Streaming, Mobile Gaming IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 31
• 32. Location-based Services Landscape IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 32
• 33. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 34. The Convergence of “ToDaClo” Touch + Data + Cloud IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 34
• 35. David Mayes ‹#›
• 36. Agenda • Some Historical Context • The Emergence of SoMoClo • The Emergence of Big Data • The Emergence of Smart Mobile • The Convergence of ToDaClo • What Do You Think? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not?
• 37. Discussion: Big Data, The Cloud, and Smart Mobile, Big Deal or Not? IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 37
• 38. My Key Takeaway Points • Even from the 50,000 foot level, a shakeout and consolidation seem inevitable • A lot of people are going to lose a lot of money • There will be “snake oil” sold that does not work • Nevertheless these three new markets are actually one unified market, and likely: The Next Big Thing IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 38
• 39. What Do You Think? • No. ToDaClo is mostly media hype, and not a “Big Deal.” • I’m skeptical. ToDaClo will probably be a “Big Deal,” but I haven’t seen much yet • Maybe. I do not know yet whether ToDaClo will be a Big Deal • Yes. ToDaClo is a Big Deal and it is already changing our lives IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 39
• 40. Thank You! IEEE UBC Okanagan Big Data, The Cloud, and Smart Mobile: Big Deal or Not? ©David Mayes 40
• 41. ©David Mayes 41

 

Can Big Data Raise Graduation Rates?

BY RICHARD NIEVA
ON APRIL 9, 2013

Collecting data and statistics is nothing new in education. Educators have been using Blackboard’s analytics software for years. But what is new is the sheer amount of predictive analytics that is available. President Obama recently announced that he wants America’s college graduate ranking to go from 12th place in the world last year to first by 2020. To accomplish this, our nation’s schools and educators will need to harness the power of big data – at least that’s what Toronto-based education startup Desire2Learn says.

The company, founded by CEO John Baker while attending the University of Waterloo, in Waterloo, Canada, in 1999, trades in educational predictive analytics. Desire2Learn, which has raised $80 million in funding from New Enterprise Associates and OMERS Ventures,  does things like help a student pick classe in which he’ll get the best grades or keep an eye on his progress. Clients include the New York City public school system as well as universities like the University of Arizona, the University of Memphis, and the Harvard School of Business. The company’s class selection software seems compelling, but for all the hoopla surrounding big data, the company will need to nail the predictive element to be really valuable.

Desire2 Learn peddles two products. The first helps students effectively pick courses toward their degrees based on how well they will likely do in them. Baker describes it as a recommendation tool a la Netflix or Amazon. It will, for instance, tell a liberal arts type how he will likely fare in an engineering class by scouring his past classwork (or high school transcripts if he’s a freshman) and compare his academic record to other students who have taken that class. Baker claims it can predict if a student will pass or not with 90 percent accuracy and even settle on his letter grade with 92 percent accuracy.

The second gathers data on how a student is actually doing in a class and spots red flags like a bad grade on a quiz, or, more subtly, rushing through an online assignment. Then a teacher can intervene, and the program can do things like suggest additional reading. For a teacher, the software can also suggest what lessons will better resonate with a student. For example, if a student does

better on a quiz after watching a certain type of video, the software can recommend a similar one.

Of course, this data-centric approach to education isn’t without pitfalls. It can serve to funnel students into the easiest courses and discourage them from challenging themselves.  Why shouldn’t a student take an engineering course even if the almighty algorithm informs him he isn’t likely to ace it? What happened to education for education’s sake?

Nevertheless, it does help in one regard.The Tennessee Board of Regents, which includes six universities including the University of Memphis and Tennessee State University, said it saw a 24 percent decrease in dropouts in one year after using Desire2Learn software. At California State University, Long Beach, the graduation rate rose 3.3 percent since deploying the software. It was the largest one-year jump for a four-year period.

In the info graphic that the company supplied below, it shows t

hat every year students graduate with about 12 credits that don’t count toward their degrees, causing them to spend more time in college, which reportedly costs taxpayers about $6 billion in the form of things like grant money and tuition subsidies, according to Complete College America.

Baker says that for a struggling student — either academically or financially — those extra units can help lead to the decision to drop out. And a high dropout rate is a data point that’s of use to no one.

Online Privacy Policy? What Online Privacy…?

A number of my students have asked me about online privacy. Many of us, not only students, have not spent the necessary time to read and research the privacy policies of the major online social media and e-commerce websites, much less to understand the implications they face with the current state of online privacy.  It is time consuming, complicated and riddled with legalese. Even if you spent the time, you probably wouldn’t understand it, so why bother?

Scott McNealy, the founder and former CEO of Sun Microsystems (now owned by Oracle), is perhaps most famous for one quote.

“Privacy? Get over it! You have no privacy!”

There is a joke that is told about valet parking at a posh restaurant.  A diner and his guest pull up to one of the finest local restaurants in front of a sign saying “valet parking.”   A very well-dressed gentlemen approaches the car and graciously opens the car doors. The gentleman accepts the keys from the driver of the late model BMW 5 Series turbo. After being seated for dinner, the diner mentions to the waiter how impressed he was with attentiveness of the valet parking staff, to which the waiter replies in shocked disbelief, ” What valet parking?”

This amusing anecdote is not so funny if you consider that is pretty close to what is happening to all of us when we visit online social media websites, or e-commerce sites.   We feel comfortable and relatively safe on well-known websites, not realizing that our BMW has been stolen by that nice gentleman with “valet parking.”  This loss of personal privacy is very real and very immediate for all of us.

“What privacy?”

Just for the record, and for whatever it is worth, the opening sentence of the privacy policy for this website reads as follows, “I have a firm belief in personal privacy, and to Internet privacy. To the extent that I can protect privacy in a cyber World dominated by large corporate self–interest, I will do my utmost to protect user privacy.”  I can do almost nothing about the privacy policies set by the global social media companies.

We know very little about the details of the personal information that has been extracted from us, how it is managed, how it is used, and with whom it is shared, and how much money has been paid for it. Perhaps we deserve a cut?  We do know that more information has been gathered on the Internet in the last two years, than in all of the previous years combined. It is beyond terabytes. It is multiple zetabytes of information and growing exponentially. The world of Big Data, for better or worse, will be built on this massive pile of personal data.

Silicon Valley’s social media industry is fighting privacy advocates over proposed California legislation, the first of its kind in the nation, that would require companies like Facebook Inc. and Google Inc. to disclose to users the personal data they have collected and with whom they have shared it.

Bonnie Lowenthal, a Democratic California assemblywoman from Long Beach (my native home town) has introduced this legislation, the “Right to Know Act.”  What is disturbing and surprising is that  the bill has caused a massive backlash against it, though it is asking for simple transparency, similar to that required for credit reporting. Google and Facebook are conspicuously silent on the “Right to Know Act,” preferring to let their industry association and unknown lobbyists speak for them.

The industry backlash against the “Right to Know Act”. It would make Internet companies, upon request, share with Californians personal information they have collected—including buying habits, physical location and sexual orientation—and what they have passed on to third parties such as marketing companies, app makers and other companies that collect and sell data.

Why are the Internet companies fighting this simple transparency so vigorously?  Google formerly trumpeted that it’s corporate watch phrase was to “do no evil.”  The industry backlash against Ms. Lowenthal’s legislation does not feel like doing no evil.

The bill highlights how lawmakers are seeking to update privacy laws. An update of a 10-year-old law focused on the direct-marketing industry, the bill could have national impact because of California’s size, and it would bring the state’s privacy practices closer to those common in Europe.

“In 2003, the biggest problem people had with privacy was telemarketing,” said Ms. Lowenthal. “Today, there are so many different mobile apps that can track location and spending habits that it’s time for an update in state law.”

I will continue to monitor this issue and report on it as it develops.

Hans Rosling Makes Visual Sense of Big Data Analytics

I started this post to make a relative mundane point for UBC Management students about the importance of making their presentations easily understandable, particularly when they involve lots of numbers or spreadsheet data. But after mulling over the post for a few days, I realized that this is a much bigger story.

Further back in my career than I prefer to admit, I had the exceptional opportunity to work with the founders of Silicon Graphics, Jim Clark, (who later went on to start Netscape with Mark Andreeson), Mike Ramsay and Jim Barton (who later started TiVo, the original PVR company). The premise of SGI was making 3D visualization ubiquitous in engineering, complex simulation, and computer animation. As often happens with the convergence of technology and great ideas, SGI was well ahead of its time. Disney loved it but the big engineering customers were not over the moon.  The concept  of 3D visualization of complex data was compelling.  Extraordinary examples of SGI visualization of tornados, molecular modelling and animation can still be found on YouTube.  But the chip technology required to achieve it, MIPS RISC (reduced instruction set computing) microprocessors) at that time, was not ready for prime time. Both MIPS and SGI are now long gone, and only SGI’s graphics computing instruction set, known as OpenGL survives.  But the era of Big Data and Visual Analytics is just beginning to emerge into the mainstream, as the technology has fully caught up.  If you have not seen this TED Talk video by Hans Rosling, it is only 4 minutes long, but it explains where we are going with Big Data, and how interpreting Big Data visually is already making a major impact on our thinking.  I have also included a reblogged post from the HBR Network which I think you will find is related to this much bigger concept.

Hans Rosling: 200 Countries, 200 Years, 4 Minutes

Reblogged from the HBR Blog Network

When Presenting Your Data, Get to the Point Fast

by Nancy Duarte  |   9:00 AM March 28, 2013

Projecting your data on slides puts you at an immediate disadvantage: When you’re giving a presentation, people can’t pull the numbers in for a closer look or take as much time to examine them as they can with a report or a white paper. That’s why you need to direct their attention. What do you want people to get from your data? What’s the message you want them to take away.

Data slides aren’t really about the data. They’re about the meaning of the data. And it’s up to you to make that meaning clear before you click away. Otherwise, the audience won’t process — let alone buy — your argument.

Take this table, for instance:

It’s confusing — especially if you project it for five seconds and then move on. And even if you leave it up for five minutes while you talk, anyone who’s struggling to derive meaning from it won’t be paying much attention to what you have to say. They’ll be too busy squinting from their seats, trying to navigate all those heavy grid lines that give every single cell equal weight. It’s not at all clear where the eye should go. Your audience won’t know what direction to read — horizontally or vertically — or what conclusions to draw. Though the Grand Total line is emphasized, is that really the main point you want to convey?

Now let’s look at the data presented more simply. Say you’ve identified three business units with potential for sustained growth in Europe. By eliminating the dense matrix and connecting only key numbers to a pie with leader lines, you remove clutter that distracts from your message. And notice the clear hierarchy of information: You can highlight important pieces of the pie by rendering them in color and their corresponding annotations in large, blue type. Other sections recede to the background, where they belong, with their neutral shades and small, gray labels.

But pie charts can be tricky for an audience to process when segments are similar in size — it’s hard to distinguish between them at a glance. If you’re running into that problem, consider displaying the same data in a linear way. In this bar chart, for example, you draw attention to the poorest-performing unit, a point that got lost in the pie:

These few tricks will help audiences see what you want them to see in your data. By focusing their attention on the message behind the numbers, not on the numbers themselves, you can create presentations that resonate with them and compel them to act.

 

5 Ways Big Data Is Going To Blow Your Mind

“Big Data, Big Deal or Not?” Debate Continues

The Gigaom Structure Data Conference has just concluded in New York City. It has added significantly to the discussion and the debate on the significance of this phenomenon.  The author, Derek Harris, has summarized my own view on the issue in his first paragraph.  The notion that Big Data is little more than business intelligence on steriods is just wrong, and those who fail to understand its importance and exploit it, may well be the losers.

5 ways Big Data is going to blow your mind and change your world

by Derrick Harris

photo: Shutterstock / GrandDuc

SUMMARY:

Call it whatever you want — big data, data science, data intelligence — but be prepared to have your mind blown. Imagination and technology are on a collision course that will change the world in profound ways.

Some people say big data is wallowing in the trough of disillusionment, but that’s a limited worldview. If you only look at it like an IT issue it might be easy to see big data as little more than business intelligence on steroids. If you only see data science as a means to serving better ads, it might be easy to ask yourself what all the fuss is about.

If you’re like me, though, all you see are the bright lights ahead. They might be some sort of data nirvana, or they might be a privacy-destroying 18-wheeler bearing down on us. They might be both. But we’re going to find out, and we’re we’re going to find out sooner rather than later.

This is because there are small pockets of technologists who are letting their imaginations lead the way. In a suddenly cliché way of saying it, they’re aiming for 10x improvement rather than 10 percent improvement. They can do that because they now have a base set of analytic technologies and techniques that are well positioned to solve, with relatively little effort, whatever data problems are thrown their way.

Here are some themes from our just-concluded Structure: Data conference that I think highlight the promise of data, but also the challenges that lie ahead.

Man and machine unite

Machine learning is already infiltrating nearly every aspect of our digital lives, but its ultimate promise will only be realized when it becomes more human. That doesn’t necessarily mean making machines think like human brains (although, granted, that’s a vision currently driving billions of research dollars), but just letting people better interact with the systems and models trying to discover the hidden patterns in everything around us.

Whatever shape it takes, the results will be revolutionary. We’ll treat diseases once thought untreatable, tackle difficult socio-economic and cultural issues, and learn to experience the world around in entirely new ways. Maybe that consumer-experience scourge known as advertising might actually become helpful rather than annoying.

That would really be something.

Man and Machine Unite

Data science, or data intelligence?

I’m not sure there needs to be a distinction between data science and data intelligence, but the latter does connote a grander goal. It’s about trying to solve meaningful problems rather than just serving ads; about trying to understand why things happen just as well as when they’ll happen. This means learning to work with smaller, messier data than we might like — certainly smaller and messier than the data sets underneath most of the massive web-company data science undertakings.

But just think about being able to go beyond predictive models and into a world of preventative — or even professorial — models. If you know what I like, where I go and who my friends are, it might be fairly easy to predict what I want to buy. Figuring out how my decision to buy something might affect my overall well-being and then telling me why? That’s a little more difficult and a lot more beneficial.

Telling stories with data

Have you ever looked at a chart and wondered what the heck it was supposed to be telling you? Or downloaded a report of your Facebook activity only to ask yourself if all the disparate data points come together to paint a bigger picture? Or tried — and failed — to stop a terrorist before his movement to recruit an army of followers gained critical mass?

A big problem with a lot data analysis right now is that it still treats data points as entities unto themselves, largely disconnected from those around them. However, data needs context in order to be really useful; it’s context that turns disparate data points into a story. Don’t just tell me how many steps I took today or the time of day I’m most active on Facebook, but tell me how that relates to the rest of my life.

And don’t just tell me that someone said he wants to kill Americans. Rather, tell me a story about how much more frequently he’s saying it and how much more inciteful his words are becoming.

The internet of things knows all

The mobile phone in your pocket is tracking your every movement and can also monitor the sounds that are surrounding you. That fitness tracker you’re wearing is identifying you by how you walk. Your smart meter data shows when you’re home, when you’re away and when you’re in the shower. Sensors in everything from toothbrushes to cars are quantifying every aspect of our lives.

This volume of data can still be a lot to deal with in terms of its volume, velocity and variety, and we’re still not quite sure what to do with it even if the right tools were in place. But all sorts of entrepreneurs, powerful institutions and intelligence agents have ideas. The technological pieces are coming along nicely, too. Just sayin’ …

This semantic life

The semantic web lives on; only it’s spreading well beyond our search engines and even our web browsers. Soon enough, we’ll be able to surface relevant content and people simply by highlighting passage of text in whatever we’re reading — web page or not — on any type of device. When we speak to our devices, they’ll not only know what we’re saying, but also what we really want even without the help of specific commands or keywords.

That’s a powerful proposition in a world where we increasingly expect our interactions to be hands-free and our answers to come as fast as our questions. Of course, what’s powerful in the hands of consumers driving in their cars or sitting on their couches iseven more powerful in the hands of doctors trying to diagnose difficult diseases or aid workers trying lend a helping hand in places where they don’t know the customs or even speak the language.

Big Data Is Still Hard, But It Gets Better

SUMMARY:When it comes to using big data, there are still bottlenecks. Many of these are around the tools that people use to try to make sense of massive amounts of information.

What’s standing between your staff and big data analysis? That was the existential question posed of DJ Patil and Jeff Hammerbacher at the GigaOM Structure:Dataevent today in New York. The two had different takes on how easy it was to give people the power to use data, with Hammerbacher, who is the co-founder of Cloudera, saying that it’s pretty simple today.

He did say that today many aspects of the input and ingress of data will end up being automated, much like systems administrators responsible for running the data center have seen many of their tasks automated.

Patil, who is now a data scientist in residence at Greylock Partners, was a bit more focused on end users. He shared his visit to a nonprofit called DoSomething.org earlier today, and said that people there had plenty of curiosity and a desire to play with data and ask questions, but they didn’t always know what to ask to get the insights they seemed to want. “We need another layer to help those people figure out what they want to ask,” he said.

From Patil’s perspective we need tools that will help us tell stories with data and let people play with it in ways that can help people come to new conclusions or see new relationships. “This is less of a machine learning problem than a ‘Can I try a bunch of things with the data?’ kind of problem,” said Patil.

And for those who are still intimidated by playing around with big data Patil has this to say, “Most people doing sophisticated analysis they don’t really know what they are doing.”

Check out the rest of our Structure:Data 2013 coverage here, and a video embed of the session follows below:

http://new.livestream.com/gigaom/structuredata

Gigaom

What’s standing between your staff and big data analysis? That was the existential question posed of DJ Patil and Jeff Hammerbacher at the GigaOM Structure:Data event today in New York. The two had different takes on how easy it was to give people the power to use data, with Hammerbacher, who is the co-founder of Cloudera, saying that it’s pretty simple today.

He did say that today many aspects of the input and ingress of data will end up being automated, much like systems administrators responsible for running the data center have seen many of their tasks automated.

Patil, who is now a data scientist in residence at Greylock Partners, was a bit more focused on end users. He shared his visit to a nonprofit called DoSomething.org earlier today, and said that people there had plenty of curiosity and a desire to play with data and ask questions, but they…

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Big Data, The Cloud And Smart Mobile Are Actually One Big Thing

ToDaClo is a current buzz word of sorts for “touch-data-cloud,” (or Big Data, The Cloud and Smart Mobile)  which appears to have been coined by a writer for Forbes magazine during a talk in Paris in May 2012.  The speaker declared the death of the previous buzz word, SoLoMo (social-local-mobile). ToDaClo does not seem to have caught on beyond France as most of the writing and blogging about it is in French.  SoLoMo had a following for some time, and even has an online manifesto, vaguely implying location based services, which have been a major mobile feature for some time in Asia, but not here.  I think the bottom line is that both of these acronyms are trying to communicate the concept that Big Data, The Cloud and Smart Mobile are inter-related.  I actually think of them as One Big Thing, even The Next Big Thing, or perhaps “Ne-Bi-Ng”  (Nebing) as some may prefer, though I doubt Nebing will ever catch on.  Sanjay Poonen, President & CEO of SAP also views them as One Big Thing.

Reblogged from Gigaom

The secret to tackling mobile, cloud and big data? Treat them as one.

by Sanjay Poonen

Sanjay Poonen, President & CEO of SAP AG

SUMMARY:It’s no secret that mobile, big data and cloud computing are transforming IT. Sanjay Poonen, president of SAP’s mobile division, says companies need a single unified strategy to tackle them, not three separate ones.

There is widespread agreement—across the globe and in every industry—that mobile, big data, and cloud computing are the three cornerstone issues of tomorrow’s business environment. In fact, a strong organizational response to each of these issues is already critical to competitive survival.

As a result, CIOs, business strategists and IT leaders are working furiously to make sure their businesses have plans in place to stay ahead of these challenges. But there is one subtlety that is frequently overlooked: When it comes to mobile computing, big data and the cloud, what we have is not three problems but one.

Rising in unison

It’s not a coincidence that the profile of these three business challenges rose in parallel. Mobile, big data, and cloud are not siloed concerns easily addressed in isolation. They exist in an overlapping matrix, where the importance of each issue increases because it leverages (or helps solve) an issue raised by one of the others.

For example, in the days before mobile computing, business users typically did all their work using just a handful of applications. Today, the average smartphone has 41 apps installed on it. And each of those applications sparks a need to consider security, since it generates data each and every time it is used. And because these devices are often connected to service provider networks – rather than directly with corporate servers – a great deal of that business app data requires secure cloud storage.

Thus the proliferation of mobile devices exacerbates the big data problem, which in turn precipitates the demand for cloud.

In short, they are all part of a single, converged and symbiotic trend. And to address them optimally requires a holistic perspective on all three.

No bottom in sight

With global demand for mobile computing at the heart of this escalation, it makes sense that IT strategists would be keenly interested in the trend lines for mobile adoption. Today, 87 percent of the world’s population owns a mobile phone; 60 million Android devices were sold in the second quarter of 2012, and now 1 million new Android devices are provisioned daily, according to Google. As of last month, there were likely more smartphones on the planet than humans, according to Cisco.

So the question is whether there is a saturation point on the horizon that could help curb this cloud/mobile/data demand? Surprisingly, no. The average number of mobile devices per employee worldwide has already reached three to five, and adoption rates continue to grow as consumers add tablets and ever-more capable smartphones to their mobile arsenals.

But consumers’ ceaseless enthusiasm for new form factors and functionality is not the whole story behind the world’s bottomless demand for mobility. Today, businesses themselves – rather than consumers – are adding fuel to the fire.

Not just a BYOD issue

As industries finally crest the hump of transforming their workflows to leverage mobile device availability, they drive new demand – not only for mobile devices, but for new scalable infrastructures that deliver more actionable intelligence from their big data.

Finance Consumer banks, operators and retailers are widely deploying mobile commerce capabilities, which, in addition to automating traditional transactions, must include on-demand access to unstructured data, such as check images.

Manufacturing  Mobile devices on the factory floor automate manual processes, thereby feeding more rapid information into the system. This makes it possible to detect and respond early to issues that take a toll on quality or productivity, such as supplier errors.

Retail  Retailers are giving regional store managers mobile app access to daily and even real-time sales performance data on the floor, allowing them to optimize displays and customer service to sell more of the most popular items.

Health care Thanks to new mobile apps and devices, the details of every patient interaction is now entered into the system nearly instantaneously. This provides a basis for a more efficient and orchestrated care response, and in some cases leading to more rapid or accurate diagnoses.

The internet of things

As mobile technology embeds itself into more and more objects, vehicles, buildings, sensors and machines, the heterogeneity of actionable business information will only grow. “Annual global IP traffic will surpass the zettabyte threshold by the end of 2016,” reports Cisco. “In 2016, global IP traffic will reach 1.3 zettabytes per year or 109.5 exabytes per month.” (As we already know, there are currently at least 2.7 zettabytes in storage globally).

Smart equipment and vehicles will upload data to service provider networks as well as private networks, and organizations will need a plan to normalize data in many forms and from many sources. The scalable infrastructures we design today to store and structure such varied data are critical to the enablement of the business innovations we will need in the future.

The effect of this convergence is already apparent, especially in the area of business intelligence. Mobile business intelligence makes it possible for organizations to provide analytics on key performance metrics to a wider variety of employees – not just for executives. Once employees get a taste for how mobile apps fuel greater effectiveness in their job duties, they will push for more dashboards and more data. And these big data stores can’t be undertaken without cloud, to facilitate real-time performance, nor mobile devices and apps, to deliver data into the field where it’s put to good use.

Embracing the Entanglement

The interdependence of mobile, big data and cloud is undeniable, and will only multiply as data growth and mobile use continue. Yet our strategic thinking lags behind the evidence. As we have learned from IT revolutions of the past, a partial strategy is worse than no strategy at all, as you can end up with an inflexible, tactical implementation that requires a ‘rip and replace’ approach.

Organizations that manage to avoid a false start with a siloed strategy will create a network design better aligned with where IT will be in five years. In short, the most successful organizations recognize the secret alliance of mobile, big data and cloud early, and develop a holistic strategy considering all three in concert.

Big Data: Big Deal Or Not?

I have been having a spirited marathon debate with a couple of my friends.  Is this alleged new “Big Data thingy” so transformational that it will change our every day lives, or is it just an evolutionary advance that may improve productivity but not much else?  The same arguments may apply to the concept of “The Cloud,” and “Smart Mobile.”  The three, taken together, are coalescing into the major information technology forces that will drive innovation and productivity into the foreseeable future.

PollDaddy: What Is Your Opinion?  Big Data: Big Deal Or Not? Or Comment Below

We are hearing regularly in the media about so-called “Big Data.”  What exactly is Big Data? A number of differing definitions have been offered from a wide range of media sources. ZDNet‘s definition is one of the best I have seen so far.  In essence, big data is about liberating data that is large in volume, broad in variety and high in velocity from multiple sources in order to create efficiencies, develop new products and be more competitive. Forrester puts it succinctly in saying that big data encompasses “techniques and technologies that make capturing value from data at an extreme scale economical”  Prior to the emergence of commercial Big Data, the concept only existed where cost was no object: in the black world of the National Security Administration, and required the largest purpose-built supercomputers in existence.

A zettabyte (symbol ZB, derived from the SI prefix zetta-) is a quantity of information or information storage capacity equal to 10²¹ bytes or 1,000 exabytes (or one sextillion (one long scale trilliard) bytes).^{[1][2][3][4][5]…..I Billion terabytes….Today, you can walk into your local computer store and buy a couple of terabyes for a $100.  Only $500 Million for a zettabyte.  In real terms that is dirt cheap, and getting cheaper daily.   Now that we have that cleared up, we can move to the next level.}

With regard to the obvious issue of personal privacy, the European Union and other organizations have made efforts to protect privacy, with very mixed results.  Other governments, notably China, are aggressively implementing opposite policies to strictly limit privacy.  Highly sophisticated telecommunications equipment has been available for years that enables deep analysis of all of your voice and Internet traffic. We learned this when Dick Cheney secretly set up such equipment to track and record all voice and data traffic in the United States.  The equipment trapped and analyzed all of it in real time. You didn’t notice a thing.  The thing about your personal data is that they already have it. Most of it comes from public sources you authorized.   I not advocating this, I am only the messenger. The founder and former CEO of Sun Microsystems, Scott McNealy famously said, “You have no privacy. Get over it.”  We must not ignore the serious issue of privacy, but the problem is already here and deep data mining is thriving.  Privacy needs a revolution of its own.

The core question then becomes whether Big Data, and for that matter, the Cloud, and Smart Mobile, represent revolutionary and transformational changes in technological capability and also consequentially, human culture, politics: how we conduct ourselves in the World.  Or is it just so many more boring zeros and ones zooming by at the speed of light, stored in chips, and processed by quantum microprocessors?  No big deal, just IT management as normal.  Frankly, this is a significant philosophical question.  For this discussion, we will focus only on Big Data.   Discussion of the Cloud and Smart Mobile will follow later.  My most recent post on Smart Mobile gives a hint of my thoughts:  Mobile Market Share: A War of Titans Worth Following, http://mayo615.com/2013/01/21/mobile-os-market-share-strategy-war-of-the-titans-worth-following/

In fairness, I cut my teeth on Marshall McLuhan‘s ideas while in university in the 1960’s.  In an amazing irony, I soon fell into Intel Corporation at the birth of the microprocessor revolution, and later, I was also present to personally participate in the emergence of the personal computer. My memory of McLuhan kept popping up everywhere.   As my career progressed, I seemed to jump onto each new wave: networking at Sun Microsystems,  then the Internet infrastructure build out explosion with Ascend Communications, and finally a host of new companies, based on Internet-based capabilities.  Through all of it, I could only conclude that somehow McLuhan, like some kind of modern Nostradamus, had foreseen it all.   Most importantly, my own life was transformed by it all, and I saw with my own eyes the massive transformation occurring all around me.

So I have no doubt that Big Data is transforming our lives, and will continue to transform our lives, in ways we cannot yet fully grasp, as I could not grasp McLuhan when I first heard him, or the significance of the Internet as I sat right in the middle of it.

I have previously described Big Data as analogous to the evolution of Chaos Theory.  For centuries, full understanding of the complexity of nature’s designs were thought to be the realm of God, and beyond human comprehension and explanation.  Then in the 1960’s in places like Santa Cruz, California and Germany, the elegant simplicity of a solution to chaos began to emerge.  The massive scale of Big Data is a very similar nut to crack. We are now seeing an elite group of data scientists and mathematicians begin to solve Big Data in a way similar to how chaos was resolved.  Google, Microsoft Bing, Baidu, Yahoo and Amazon are driving the development of these mathematical skill sets.

Last year I showed my UBC Faculty of Management students a YouTube video on Data Mining. In the video, the two Hungarian mathematicians leading a data mining company, described how they had solved hideously complex problems that were previously beyond any computational solution. The key to their success was their ability to extract very precise useful information from extraordinarily large stores of information.  The metaphor here is more like finding a particular grain of sand on a very large beach.  A parallel key factor has been the incessant march of Moore’s Law.  Even 10 years ago, successful data mining on this scale could not have been accomplished. The computational cycles and high speed mass storage were not available or were too expensive.   Today those microprocessor cycles are available.  The costs will continue to plummet, making further advances inevitable. Failure to consider Moore’s Law and available computational cycles has also been the cause of many failed ideas over the years. But the threshold has arrived.

Today, developments like Google Spanner, the largest known database architecture in the World, have joined with the computational solutions.

Unveiled this fall after years of hints and rumors, it’s the first worldwide database worthy of the name — a database designed to seamlessly operate across hundreds of data centers and millions of machines and trillions of rows of information.

Spanner is a creation so large, some have trouble wrapping their heads around it. But the end result is easily explained: With Spanner, Google can offer a web service to a worldwide audience, but still ensure that something happening on the service in one part of the world doesn’t contradict what’s happening in another.

Google’s decision to reveal Spanner has many dimensions.  First, it provides a peek into the black World of the U.S.  National Security Agency and the U.S. Defense Intelligence Agency.  Previously, the existence of such large and sophisticated global databases were only imagined. We now know they exist and are a crucial component of Big Data.

Read more in my post, Google Spanner, the single largest database in the world

http://mayo615.com/2012/11/26/inside-google-spanner-the-single-largest-database-in-the-world/

For me, the most compelling example of how this all works, has been the extremely sophisticated Big Data mining used by the Obama campaign to achieve re-election. As early as March 2012, the Wall Street Journal began reporting about “Dashboard,”  the Obama campaign app that was mining Big Data to find undecided voters in key states.  But not only undecided voters.  Dashboard can key in, find and persuade “Off the Grid” voters.  Off the Grid is the term used to describe those people, such as students and other young people, with constantly changing locations and only a mobile phone.  These voters have historically been virtually impossible to reach.  This short PBS Newshour video below speaks volumes about the extraordinary impact and value of Big Data, not seen before.

Watch How Much Do Digital Campaigns Know About You? on PBS. See more from PBS NewsHour.

The campaign’s hiring of Rayid Ghani, as “chief data scientist,” and an army of data analysts, set the stage for what was to come.  On election night, Mitt Romney and Paul Ryan were absolutely convinced that they had won the election, but were shocked to find otherwise. Working through their disbelief, both candidates later remarked about the enormous voter turnout for Democrats in key locations and the “technology advantage” of the Obama campaign.

So from my years of observation of the march of technology and its impact on my own life, I am convinced that we are entering another transformational period as profound as the emergence of the Internet itself.

I have been repeatedly drawn back to Steve Job’s 2005 Stanford University commencement address, in which he closes with references to Stuart Brand and The Whole Earth Catalog. Stuart Brand is an extraordinary futurist.  One of Ken Kesey’s original Merry Prankster’s chronicled in Tom Wolfe’s book non-fiction novel, The Electric Kool-Aid Acid Test, Brand had been inspired by the legendary first photograph of the entire Earth taken by Apollo 8 astronaut Frank Borman.  Brand is also the founder of The Well,  the very early Sausalito-based Internet Service Provider, who is now considered one of the most important thinkers on human culture, technology and its impacts.  Word of Job’s commencement address spread virally around the Valley...”Did you hear what Job’s said at Stanford today?”    Steve was basically saying that he too understood what McLuhan had said, and that Stuart Brand also understood the transformational importance of the Global Village, by publishing The Whole Earth Catalog.

Reachli

Reachli is a startup to watch. I saw the former Pinerly present at Plug & Play in Sunnyvale last August, and met the founders, when our UBC FOM student, Jonas Fung, hosted a Canadian startup event at Plug & Play. Reachli came out of U of Toronto.. Needless to say, I was impressed… The business model at the time was a blend of Web analytics and viral marketing, with a tag line about “turning browsers into buyers,” which has been the bane of social media marketing efforts. The conversion rate is abysmal. I “got it” immediately,and I am pleased to see them moving forward.. Good luck Reachli!