Internet’s Most-Read Stories (Infographic)

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Fast Company:

It turns out that the most-shared articles aren’t fluffy clickbait. Generally, they’re pieces that focus on grander themes: kids (“Schools Fail to Train Kids”), extreme wealth and poverty (“The World’s Poorest President,” “The Rich Alarmed by Homeless Jesus”), self-improvement (“What Mentally Strong People Avoid,” “How Not to Say the Wrong Thing”), God (“Science Increasingly Makes the Case for God”), and death (“Dying on Your Own Terms,” “Unmournable Bodies: Those We Kill Unknowingly”). Only some of the most universal aspects of human experience.

The visualization also reveals what types of storytelling are most engaging. Readers shared stories about other people’s lives the most when they were told from an intimate perspective instead of with impersonal statistics—as seen in the story of the life of Dasani, a homeless child from New York City, or a new mother who drove a Mercedes to pick up food stamps. If it’s not a personal, emotionally driven story, then it’s probably useful or service-y (“14 Habits That Drain Your Energy”) or entertaining (“Justin Timberlake Shows Us How Dumb We Sound When We Use Hashtags”).

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6 Bad Digital Habits and How to Overcome Them (Infographic)

Digital_BadHabits_Infographic

Source: Digital Information World

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CEOs Embrace Digital Transformation, Compete in New Industries

CEOs no longer question the need to embrace technology at the core of their business in order to create value for customers, but 58% still see the rapid pace of technological change as a challenge. So we learn from the 18th annual PwC CEO survey. It’s based on 1,322 interviews with CEOs in 77 countries, conducted between September and December 2014.

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Digital transformation is both a challenge and an opportunity. Digitization has blurred or even eliminated rigid industry boundaries starting with the media, content, and communications industries and now spreading everywhere. The new digital business world has no pre-defined boundaries, no industry-based rules or limitations.

Indeed, 54% of CEOs have entered a new sector or sub-sector, or considered it, in the past three years, according to PwC. More than half (56%) of CEOs think it likely that companies will increasingly compete in new industries over the next three years. Unlike in the past, when “unrelated diversification” was the business strategy of only large conglomerates, PwC found that 51% of the smaller firms (revenues up to $100 million) included in the survey, have entered a new sector or subsector, or considered doing so, within the past three years, compared with 64% of the largest firms, with revenues of over $10 billion.

What technologies CEOs think are the most strategic in facilitating the digital transformation of their companies and industries? Leading the list are mobile technologies for customer engagement (81%), data mining and analysis (80%), cyber security (78%), the Internet of Things (65%), socially enabled business processes (61%) and cloud computing (60%). Most interesting here is the inclusion of the Internet of Things, somewhat new on the scene as a business buzzword, but it’s possible that the survey respondents have either referred to what they see as its future potential or to the value they have already derived from established technologies such RFID and machine-to-machine communications.

The pace of digital transformation has a lot to do with the return on investment CEOs and their companies have enjoyed from the digital technologies they have deployed in the past. 86% say a clear vision of how digital technologies can help achieve competitive advantage is key to the success of digital investments. 83% say the same for having a well-thought-out plan – including concrete measures of success – for digital investments.

The majority of CEOs think that digital technologies have created high value for their organizations in areas like data and data analytics, customer experience, digital trust and innovation capacity. Surprisingly, however, most CEOs point to operational efficiency as the area where they have seen the best return on digital investment.  82% think value has been created in this area, with half of these CEOs seeing “very high value.”  The PwC report explains this finding as follows: “The transformation of cost structures is a symptom of the digital transformation that companies are undergoing as they align their business and operating models to new ways of delivering stakeholder value. Indeed, 71% of CEOs also tell us they’re cutting costs this year – the highest percentage since we began asking the question in 2010.”

US-CEO-Survey-Digital-Technology-graphic

It’s clear from these findings that digital technologies are used not only for generating new revenue streams from existing or new customers, sometimes in completely new lines of business, but also as tools CEOs used to automate existing work flows (and reducing headcount) and streamlining existing business processes. To make sure digital technologies are deployed for both expansion and efficiency, CEOs now understand that they need to take charge: 86% think it’s important that they themselves champion the use of digital technologies.

This is certainly good news and what’s driving the acceleration of the digital transformation of all businesses.

For more, check out these survey reports

http://www.pwc.com/us/en/ceo-survey/index.html?WT.mc_id=cs_us-hero-home_CEO-survey for the full report

http://www.pwc.com/us/en/ceo-survey/technology-impact.jhtml for digital technology-specific stats

[Originally published on Forbes.com]

 

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The Hadoop Bubble Quivers As Hortonworks Misses

Hadoop BubbleLast month, Hortonworks announced quarterly results for the first time as a public company and they came below expectations. It had revenues of $12.7 million (up 55% year-over-year), but average Wall Street estimates were $13.42 million. Similarly, Wall Street expected a loss of $2.04 per share and Hortonworks reported a loss of $2.19 per share.

The results could be attributed to a company new to the game of providing guidance to Wall Street. But the company’s management had substantial experience in that department throughout their impressive careers so we must look somewhere else for an explanation. What if November 10, 2014, the day Hortonworks filed the paperwork for its IPO was the beginning of the end of the Hadoop bubble, to quote your humble correspondent? What if December 12, 2014, the day Hortonworks went public, surprising many by its swift action, the bubble “began to quiver and shake preparatory to its bursting”? What if Hortonworks had decided to rush to the exit while expectations were high?

People who had over-inflated expectations—and may have grumbled yesterday “what were we thinking”—should have listened to Mike Stonebraker last August. Here’s what this foremost authority on databases (and serial entrepreneur) said about the new generation of Hadoop from Hortonworks competitor Cloudera:

Impala is architected exactly like all of the shared-nothing parallel SQL DBMSs, serving the data warehouse market. Specifically, notice clearly that the MapReduce layer has been removed, and for good reason. As some of us have been pointing out for years, MapReduce is not a useful internal interface inside a SQL (or Hive) DBMS. Impala was architected by savvy DBMS developers, who know the above pragma. In fact, development activity similar to Impala is being done by both HortonWorks and FaceBook. This, of course, presents the Hadoop vendors with a dilemma. Historically, “Hadoop” referred to the open source version of MapReduce written by Yahoo. However, Impala has thrown this layer out of the stack. How can one be a Hadoop vendor, when Hadoop is no longer in the mainstream stack? The answer is simple: redefine “Hadoop”, and that is exactly what the Hadoop vendors have done. The word “Hadoop” is now used to mean the entire stack.

In my post, I suggested “a few things to ponder when considering the potential success of the current leading Hadoop vendors and whether Hadoop in general is in the first stage of a rapid market expansion or the last stage of a bubble inflating.” One of them was the incorporation of Hadoop and similar tools by established software vendors into their traditional database and information management offerings.  Stonebraker is highlighting the opposite, the recasting of Hadoop into what looks like a traditional database technology. He says: “Meanwhile most of the data warehouse vendors support HDFS, and many offer features to support semi-structured data. Hence, the data warehouse market and the Hadoop market will quickly converge.”

Another argument I made was “Hadoop is so 2004 (at least at Google).” Here’s Stonebraker on the subject:

Google must be “laughing in their beer” about now. They invented MapReduce to support the web crawl for their search engine in 2004. A few years ago they replaced MapReduce in this application with BigTable, because they wanted an interactive storage system and MapReduce was batch-only. Hence, the driving application behind MapReduce moved to a better platform a while ago. Now Google is reporting that they see little-to-no future need for MapReduce. It is indeed ironic that Hadoop is picking up support in the general community about five years after Google moved on to better things. Hence, the rest of the world followed Google into Hadoop with a delay of most of a decade. Google has long since abandoned it. I wonder how long it will take the rest of the world to follow Google’s direction and do likewise…

No matter. Here’s what Matthew Hedberg, an analyst for RBC Capital Markets, wrote (according to Investor’s Business Daily) just before the Hortonworks quarterly earnings announcement:  “We remain bullish on Hortonworks’ opportunity as a pure play on Hadoop and believe it to be one of the better-positioned disruptive vendors in what could be a once-in-a-decade data replatforming opportunity.” An analyst with Cowen and Co, Jesse Hulsing, expressed a similar bullish sentiment: “The Hadoop market is in early stages of adoption. Our view is that most large enterprises (5,000-plus employees) will have adopted or piloted the technology by fiscal year 2020. The underlying driver of this adoption is the growth in analytic applications, which is driven by rapid growth in new data types and new user types. Hortonworks should benefit from this.”

Maybe the market is indeed going gangbusters and Hortonworks is simply losing to better-equipped competitors, primarily Cloudera?

Apparently anticipating this question, Cloudera issued last week a “momentum press release,” announcing that its 2014 revenues “surpassed $100 million,” calling the results “an indicator of Hadoop’s strong momentum.” Derrick Harris at GigaOm had this to say about the news: “That the company, which is still privately held, would choose to disclose even that much information about its finances speaks to the fast maturation, growing competition and big egos in the Hadoop space.”  Similarly, Arik Hesseldahl at Re/Code noted that a “likely motivation for the press release is a battle of optics between Cloudera and its primary rival, Hortonworks… Cloudera may simply be seeking to remind the marketplace which Hadoop company is bigger.”

It is also reminding the marketplace that it’s not going to be subject to the scrutiny accorded public companies anytime soon. Cloudera co-founder and chief strategy officer Mike Olson told Re/Code: “We have no timeline for an IPO, period.” CEO Reilly told Fortune “We’re of the size and scale that we could be a successful public company right now. But we’re so well backed that we don’t need to go public to have access to financing.” Indeed, after riding a bubble and raising a cool $1 billion, who needs Wall Street?

But they need Main Street. Regardless of the close to $1.5 billion in venture capital the key Hadoop competitors left standing—Cloudera, Hortonworks and MapR—have raised, to survive and succeed they need enterprise customers to buy the current (and future) Hadoop incarnations they offer.

In my previous post on the Hadoop Bubble, I quoted a 2014 survey conducted by Wikibon which found that only 36% of the respondents were using Hadoop and the majority of those (64%) were using it in proof-of-concept environments.  Even more important to the financial future of Hadoop vendors, Wikibon found that “only 25% of Hadoop practitioners are paying customers of one or another Hadoop vendor. 24% use a free distribution provided by a vendor, but the majority, 51%, roll their own Hadoop downloaded from the Apache Software Foundation.” Don’t you think this has something to do with Hortonworks’ quarterly results?

The author of the excellent Wikibon report, Jeff Kelly, gave a presentation last week, titled The Big Data Money Trail. About 23 minutes into the presentation, Kelly gets to a slide titled (surprise!) “Is this the beginning of the end of the bubble, or is there something next that matters?”

Kelly definitely thinks (or at least thought last week) that Hadoop still matters. He thinks Cloudera and Hortonworks will survive and doesn’t back down from his previous estimates of how big the big data market will get. He predicts three future developments, all helping accelerate big data adoption, but not necessarily (in my opinion) promising for Hadoop vendors: enterprises will overcome their process and culture obstacles for adopting big data technologies; innovation will continue to drive the market because it is based on open source software; and while Hadoop was the “low-hanging fruit,” offering cost saving opportunities, now enterprises will start building “data-driven applications.”

To illustrate the last point, specifically the value that can be created by all these new applications of big data, Kelly reproduced on the slide the results of previous work done by Wikibon which estimated the “spend and value delivered by industrial internet” to reach $1.2 trillion in 2020. Bert Latamore, his colleague at Silicon Angle, wrote in his summary of Kelly’s talk that “Vendors will do well in the Big Data market over the next decade, Kelly predicts, but the real winners will be the companies that harness the technology creatively. He estimates that practitioners will create $1.2 trillion in new value from Big Data over the coming decade.” (Italics mine)

So a 2013 report on the Industrial Internet has metamorphosed into current (and misattributed) estimates of how many dollars are swimming in the big data lake. This is how bubbles rise, and eventually, burst.

Or maybe not, maybe I’m wrong and what we have is the beginning of a solid market for products from disruptive vendors going after “once-in-a-decade data replatforming opportunity.”  After all, Hortonworks provided above-consensus guidance for the current quarter and they are much closer than I to what is really happening in the marketplace.

In an interview with Derrick Harris conducted last week, Hortonworks CEO Rob Bearden said that he is not backing off his 2014 prediction that Hadoop will soon become a multi-billion-dollar market and Hortonworks will be a billion-dollar company in terms of revenue. Hadoop is actually just a part — albeit a big one — of a major evolution in the data-infrastructure space, he explained to Harris. As companies start replacing the pieces of their data environments, they’ll do so with the open source options that now dominate new technologies. These include Hadoop, NoSQL databases, Storm, Kafka, Spark and the like. “Open source companies can be very successful in terms of revenue growth and in terms of profitability faster than the old proprietary platforms got there,” Bearden said.

 Originally posted on Forbes.com

 

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Health Care and IT: The Long Road to Wellness

HealthCareIT_Cartoon“The development of our information processing industry is basically governed by longer term super-cycles… Analyses of what computational environments will facilitate can be mind-boggling. To offer just one example, health care delivery will be revolutionized by 1990, with most large metropolitan areas having implemented vertically-integrated health facilities coordinated by computer… [including] physicians’ offices, neighborhood health care centers, hospitals, university medical centers, nursing homes, rehabilitation centers and home health care”–Gideon Gartner, 1978

“Health care lags behind other industries in adopting information technology by as much as 10–15 years… In 2020, a forecast of widespread use of computers in health care within 15 years might finally be valid”–Peter Goldschmidt, 2005

“As Medicare chief, [Dr. Donald M. Berwick] has pushed doctors and hospitals to adopt electronic health records, merge their operations and coordinate care to eliminate medical errors that kill thousands of patients each year. If his estimate is right, Medicare and Medicaid could save $150 billion to $250 billion a year by eliminating waste, which he defines as ‘activities that don’t have any value.’”–Robert Pear, “Health Official Takes Parting Shot at ‘Waste’,” The New Work Times, December 3, 2011

“The controversy and contradictions started when Thomas Eric Duncan first was admitted to the emergency department at Texas Health Presbyterian Hospital Dallas Sept. 25. He told his nurse he had been in Africa prior to his arrival in the U.S. The information, THR officials say, was entered into the EHR, but the information somehow did not reach the appropriate clinicians. Duncan was then discharged from the ER that day, only to return to the hospital’s ER four days later, where he was then diagnosed with the Ebola virus. THR declined to comment further. The chain of events has sparked public debate amongst clinicians and IT professionals over whose mistake caused the failure to communicate Duncan’s critical travel history to physicians.”–Erin McCann, HealthcareIT News, October 6, 2014

“A 2013 RAND survey of physicians found mixed reactions to electronic health record systems, including widespread dissatisfaction. Many respondents cited poor usability, time-consuming data entry, needless alerts and poor work flows…  Even in preventing medical mistakes — a central rationale for computerization — technology has let us down. A recent study of more than one million medication errors reported to a national database between 2003 and 2010 found that 6 percent were related to the computerized prescribing system… The unanticipated consequences of health information technology are of particular interest today. In the past five years about $30 billion of federal incentive payments have succeeded in rapidly raising the adoption rate of electronic health records. This computerization of health care has been like a car whose spinning tires have finally gained purchase. We were so accustomed to staying still that we were utterly unprepared for that first lurch forward.”–Robert M. Wachter, The New York Times, March 22, 2015

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The Apple Watch, Uber, and Robotic Car Service

apple-watch-uberTech Crunch: “When you open the Uber app on your Apple Watch, it goes straight to a screen showing how long it’ll be until a car can come get you — no pulling out your phone to drop pins or choose between Uber X, Uber Pool, or black car service.”

The efficiencies of ride sharing will get another boost, on the supply side, when Uber and Google will substitute robots for drivers. Here’s the forecast from ABI:

Car and ride sharing is just one example of the new on-demand economy allowing real-time matching of supply and demand through connected smartphone applications. According to ABI Research, successive forms of vehicle sharing approaches represent paradigm shifts in uptake and popularity; each new generation seeing adoption rates at least an order of magnitude larger than the previous:

  • Car Sharing 1.0 – Street Rental Service: Cars parked on the street can be located, unlocked, used, and left behind. Examples: Zipcar, car2go, DriveNow.
  • Car Sharing 2.0 – Ride Sharing Taxi Service and Carpooling: Private drivers picking up customers using their privately owned vehicles. Examples: Uber, Lyft, Sidecar, Carpooling.com, BlaBlaCar.
  • Car Sharing 3.0 – Robotic Car Service: Driverless cars which can be called remotely and used without a driver on board.

ABI-RideSharing-Forecast

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Big Data and Healthcare (Infographic)

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From Steve Lohr’s @SteveLohr profile of Jeff Hammerbacher  in the New York Times

On the Case at Mount Sinai, It’s Dr. Data

Jeffrey Hammerbacher is a number cruncher — a Harvard math major who went from a job as a Wall Street quant to a key role at Facebook to a founder of a successful data start-up.

But five years ago, he was given a diagnosis of bipolar disorder, a crisis that fueled in him a fierce curiosity in medicine — about how the body and brain work and why they sometimes fail. The more he read and talked to experts, the more he became convinced that medicine needed people like him: skilled practitioners of data science who could guide scientific discovery and decision-making.

Now Mr. Hammerbacher, 32, is on the faculty of the Icahn School of Medicine at Mount Sinai, despite the fact that he has no academic training in medicine or biology. He is there because the school has begun an ambitious, well-funded initiative to apply data science to medicine.  …

Jeffrey Hammerbacher now leads a team that uses quantitative skills to improve medical treatments. His move from the start-up world was inspired by his own health crisis.

“We’re pursuing problems that are computationally and intellectually exciting, and where there is the potential to change how doctors treat patients in two or three years,” Mr. Hammerbacher said.

Eric Schadt, the computational biologist who recruited Mr. Hammerbacher to Mount Sinai, says the goal is to transform medicine into an information science, where data and computing are marshaled to deliver breakthroughs in the treatment of cancer, Alzheimer’s, diabetes and other chronic diseases. Mount Sinai is only one of several major medical schools turning to data science as a big part of the future of medicine and health care.

They are reaching out to people like Mr. Hammerbacher, whose career arc traces the evolution of data science as it has spread across the economy. After a job designing trading models at Bear Stearns, he worked for a few important years at Facebook, where he started the social network’s data team and made his reputation and a tidy sum. Next, he was one of four founders of Cloudera, a fast-growing company that makes software tools for data science. And now he is immersed in medicine.  …

Dr. Schadt had concluded that medicine was ripe for a data-driven revolution. Chronic diseases, Dr. Schadt explained, are not caused by single genes, but are “complex networked disorders” involving genetics, but also patient characteristics such as weight, age, gender, vital signs, tobacco use, toxic exposure and exercise routines — all of which can be captured as data and modeled.

“We are trying to move medicine in the direction of climatology and physics; disciplines that are far more advanced and mature quantitatively,” he said.

That message resonated with Mr. Hammerbacher. By 2013 he was spending most of his time in New York rather than on the West Coast, assembling a research team that now numbers 10 people. Their expertise spans the breadth of data science: machine learning, data visualization, statistics and programming.

His group’s objective is to alter how doctors treat patients someday. For example, Mount Sinai medical researchers have done promising work on personalized cancer treatments. It involves the genetic sequencing of a patient’s healthy cells and cancer tumor. Once the misbehaving gene cluster is identified and analyzed, it is targeted with tailored therapies, drugs or vaccines that stimulate the body’s defenses.

Mr. Hammerbacher’s team does not do the basic science. Other researchers do that. His group works on the “computational pipeline,” he said, with the goal of making personalized cancer treatments more automated and thus more affordable and practical. “It’s ultimately what cancer cures are going to look like,” he said.

The road to technology revolutions is paved with failure, halting progress and hard work. Mr. Hammerbacher and his colleagues are engaged in pathbreaking yet often frustrating data science work.

He is optimistic about his initiative’s prospects, but has come to appreciate that the mysteries of the human body may be more resistant to math than finance or social networks are. Today he speaks less about quants taking over than about their lending a hand. “We’re not the most important people,” he said, “but we can help.”

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The Age of Context Quantified

AmbientIntelligence

 

Ambient intelligence is a relatively new term in the technology lexicon, yet ABI Research forecasts that it will become the major evolution in technology-based consumer services and quality of life applications over the next 10 years. Essentially, ambient intelligence is the ability of a system to appreciate its environment, be aware of the user (and other people / objects) within that environment and most importantly, interpret and respond to their needs, unprompted.

Senior Analyst Patrick Connolly comments, “In technology terms ambient intelligence is the unification of hot new areas such as neural networks, big data, IoT, connected home, wearables, device user interfaces, and health / fitness, into services that can automate processes and make recommendations to improve the users quality of life. A major aspect in enabling this is the arrival of new location technologies such as BLE beacons, LED / VLC, sensor / data fusion, LTE-direct, Wi-Fi 2.0, etc.”

“The applications of ambient intelligence are multitude, but on the consumer side, the big drive is the battle for next generation search and evolved personal assistant applications that can predict the needs of their users and make changes / recommendations to facilitate these needs. From an application point of view, ABI Research forecasts over 8 billion ambient intelligence related application downloads in 2020, primarily focused on personal assistant, social, health / fitness, augmented reality, and local search / discovery applications.”

These findings are part of ABI Research’s Location Based Services Market Research.

Ambient Intelligence or what Robert Scoble and Shel Israel call The Age of Context:

[slideshare id=39285195&doc=samsungscoble-140919063950-phpapp01]

 

 

 

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Growing the digital business (infographic)

14-6325 - Mobility Research Infographic_v10

 

Source: Accenture Mobility Research 2015

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Net Neutrality Means Different Things to Different People (Infographic)

net-neutrality-definedSource: Defining Net Neutrality Without the Politics and Net Neutrality’s Technical Troubles

 

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