Whats the Big Data

Use of IoT in Healthcare and Life Sciences

Posted on January 11, 2016 by GilPress

IoT_healthcare

Despite numerous regulatory and privacy constraints, organizations inside and outside the healthcare industry are exploring ways to put the IoT to work. Players include pharma and biopharma manufacturers; hospitals and clinics; physicians, nurses and other healthcare providers (HCPs); health insurers; fitness companies; and tech firms. The goals are to cut costs, boost efficiency and improve the way illnesses are diagnosed, treated and prevented.

At the same time, an increasing number of digitally empowered consumers are taking more responsibility for their health. Primed to use fitness wearables and smartphone apps, people are growing more comfortable with new types of sensors that capture and analyze their health and medical data. It will only be a matter of time before this information is seamlessly integrated into larger healthcare systems to make their care more precise and efficient.

Though their number is growing steadily, many IoT healthcare projects are still in their infancy, and remain a patchwork of disparate and isolated initiatives. And while it’s not clear yet how things will shake out, there is also no shortage of ideas. Many large and influential tech firms—including Apple, Google (and its parent company Alphabet), Samsung, Philips, IBM, General Electric and SAP—have entered the IoT space in a big way and are hoping to make things happen quickly.

The result is that hospitals and healthcare systems are using the IoT to make their facilities more efficient. Initiatives include sharing records to ensure higher-quality care, tracking medical supply inventory and communicating with field personnel.

Many pharma companies and medical device makers are already incorporating IoT components into their manufacturing and distribution operations. They are also exploring more strategic ways to harness it to make their products better during the research and development phase and in clinical trials.

Posted in Internet of Things, Misc | Tagged emarketer, Healthcare, life sciences | Leave a comment

The Machine Learning Landscape

Posted on January 9, 2016 by GilPress

MachineIntelligenceLandscape

Shivon Zilis:

Most of these machine intelligence startups take well-worn machine intelligence techniques, some more than a decade old, and apply them to new data sets and workflows. It’s still true that big companies, with their massive data sets and contact with their customers, have inherent advantages—though startups are finding a way to enter.

Achieving autonomy

In last year’s roundup, the focus was almost exclusively on machine intelligence in the virtual world. This time we’re seeing it in the physical world, in the many flavors of autonomous systems: self-driving cars, autopilot drones, robots that can perform dynamic tasks without every action being hard coded. It’s still very early days—most of these systems are just barely useful, though we expect that to change quickly.

These physical systems are emerging because they meld many now-maturing research avenues in machine intelligence. Computer vision, the combination of deep learning and reinforcement learning, natural language interfaces, and question-answering systems are all building blocks to make a physical system autonomous and interactive. Building these autonomous systems today is as much about integrating these methods as inventing new ones.

The new (in)human touch

The virtual world is becoming more autonomous, too. Virtual agents, sometimes called bots, use conversational interfaces (think of Her, without the charm). Some of these virtual agents are entirely automated, others are a “human-in-the-loop” system, where algorithms take “machine-like” subtasks and a human adds creativity or execution. (In some, the human is training the bot while she or he works.) The user interacts with the system by either typing in natural language or speaking, and the agent responds in kind.

These services sometimes give customers confusing experiences, like mine the other day when I needed to contact customer service about my cell phone. I didn’t want to talk to anyone, so I opted for online chat. It was the most “human” customer service experience of my life, so weirdly perfect I found myself wondering whether I was chatting with a person, a bot, or some hybrid. Then I wondered if it even mattered. I had a fantastic experience and my issue was resolved. I felt gratitude to whatever it was on the other end, even if it was a bot.

On one hand, these agents can act utterly professional, helping us with customer support, research, project management, scheduling, and e-commerce transactions. On the other hand, they can be quite personal and maybe we are getting closer to Her — with Microsoft’s romantic chatbot Xiaoice, automated emotional support is already here.

As these technologies warm up, they could transform new areas like education, psychiatry, and elder care, working alongside human beings to close the gap in care for students, patients, and the elderly.

Posted in AI, Machine Learning, Misc | Leave a comment

IIA, Forrester, IDC, and Gartner on the Future of Big Data Analytics and Cognitive Computing

Posted on January 9, 2016 by GilPress

CognitiveComputing

Big data analytics is the next trillion-dollar market, says Michael Dell. IDC has a more modest and specific prediction, forecasting the market for big data technology and services to grow at a 23.1% compound annual growth rate, reaching $48.6 billion in 2019.

The larger market for business analytics software and business intelligence solutions which now includes the new disciplines of data science and cognitive computing (e.g., IBM Watson) is at least 5 times bigger. But a much larger market, which may indeed approach a trillion dollar sometime in the not-distance future, includes the revenues companies in any industry will generate from “monetizing” their data and algorithms.

Here’s my summary of predictions for big data analytics and cognitive computing from the International Institute for Analytics (IIA), Forrester, IDC, and Gartner.

Big data analytics will be embedded everywhere

IIA predicts that computing will become increasingly microservice-enabled, where everything – including analytics – will be connected via an API. IDC predicts that by 2020, 50% of all business analytics software will include prescriptive analytics built on cognitive computing functionality and that Cognitive Services will be embedded in new apps. Embedded data analytics will provide U.S. enterprises $60+ billion in annual savings by 2020.

Goodbye data preparation, hello data science

IIA predicts that automated data curation and management will free up analysts and data scientists to do more of the work they want to do. Forrester says that in 2016, machine learning will begin to replace manual data wrangling and data governance dirty work, and vendors will market these solutions as a way to make data ingestion, preparation, and discovery quicker. Through 2020, according to IDC, spending on self-service visual discovery and data preparation tools will grow 2.5x faster than traditional IT-controlled tools for similar functionality.

The meager supply of people with the right data analysis skills will continue to baffle experts

Automated data preparation will help address the limited supply of analysts and data scientists. However, opinions differ regarding when supply will start meeting demand. The talent crunch, says IIA, will ease as many new university programs come online and it will stop being a challenge for large corporations—they will find ways to address their requirements for number-crunching, model-spewing staff.

No, says IDC, the shortage of skilled staff will persist and extend from data scientists to architects and experts in data management. As a result, the market for big data professional services will expand rapidly, with a CAGR of 23% through 2020. Forrester agrees that the “huge demand” will not be met in the short term, “even as more degree programs launch globally.” In 2016, Forrester predicts, firms will turn to insights-as-a-service providers and data science- as-a-service firms and to labor-savings options such as algorithm markets and self-service advanced analytics tools.

There’s risk in them thar data hills

Gartner predicts that due to the volume and variety of data and the sophistication of advanced analytics capabilities, the risks associated with big data analytics projects will continue to be larger than those associated with typical IT projects. In addition, by 2018, 50% of business ethics violations will occur through improper use of big data analytics, according to Gartner. Forrester highlights some of the risks associated with the ever-changing big data vendor hype, predicting that half of all “big data lake” investments will stagnate or be redirected. Forrester also warns that immature data science teams will improperly exploit algorithm markets, and spend precious time either developing an algorithm they could have bought or trying to apply an algorithm incorrectly.

We will have a new buzzword

Cognitive technology will become the follow-on to automated analytics, predicts IIA. For many enterprises, the association between cognitive computing and analytics will solidify in much the same way that businesses now see similarities between analytics and big data. IIA adds to the mix yet another term, predicting also that data science and predictive/prescriptive analytics will become one and the same.

How about going back to “data mining”?

Data monetization will take off

By 2020, IDC predicts, data monetization efforts will result in enterprises increasing the marketplace’s consumption of their own data by 100-fold or more. Also by 2020, the amount of data that is worth analyzing will double. Forrester predicts that as firms will try to sell their data, “many will sputter.” In 2016, an increasing number of firms will look to drive value and revenue from their “data exhaust.” Only 10% of enterprises took their data to market in 2014, but 30% reported data commercialization efforts in 2015, a 200% increase.

Forrester declares that “all companies are in the data business now.” IDC predicts that by 2020, organizations able to analyze all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their less analytically oriented peers. A similar figure for revenues associated with data monetization will get us closer to Michael Dell’s trillion-dollar prediction. In the same interview, Dell described the current state of data mining/predictive analytics/data science/prescriptive analytics/cognitive computing: “If you look at companies today, most of them are not very good at using the data they have to make better decisions in real time.”

Sources

IIA

2016 analytics priorities and predictions webinar

2016 analytics priorities and predictions research brief

Forrester

Predictions 2016: The Path From Data To Action For Marketers

IDC

IDC On-Demand Webcasts: Worldwide Big Data and Analytics 2016 Predictions

New IDC Forecast Sees Worldwide Big Data Technology and Services Market Growing to $48.6 Billion in 2019, Driven by Wide Adoption Across Industries

Gartner

Gartner Says Customer Data Has Monetary Value but Many Organizations Ignore It

Gartner Says, By 2018, Half of Business Ethics Violations Will Occur Through Improper Use of Big Data Analytics

Originally posted on Forbes.com

Posted in Big Data Analytics, Misc, Predictions | Tagged Forrester, Gartner, IDC, IIA | Leave a comment

Most In-Demand Data Science Skills

Posted on January 9, 2016 by GilPress

Data-Science-Skills2016

Source: CrowdFlower, based on “3500 relevant job openings from LinkedIn.”

The folks at CrowdFlower excluded Excel from their list but noted that “that’s still something you see in myriad job listings. Old habits die hard.” Of course, data scientists don’t want to associate the “sexiest job of the 21st century” with old habits. Employers, however, want to cover all bases, sexy or not.

Posted in Data Science, Data Science Careers, Data Scientists, Misc | Tagged CrowdFlower | Leave a comment

Remembrance of Technology Past in 2030

Posted on January 8, 2016 by GilPress

Tech_in2030

Source: @ValaAfshar

Posted in Misc | Tagged skype, YouTube | Leave a comment

Music streaming grew 93% in 2015

Posted on January 7, 2016 by GilPress

music_streaming_2015

Nielsen:

…on-demand audio and video streaming continued to gain in popularity in 2015, posting growth rates of 83% and 102%, respectively. In fact, Justin Bieber’s album Purpose set an all-time record for total audio on-demand streams when it was streamed more than 100 million times the week of its release.

In the physical realm, vinyl stayed strong, as sales of LPs hit a new record in 2015—nearly 12 million units. This marks the 10^th straight year of vinyl sales growth. The big winners in this realm were independent record stores, which drove 45% of all vinyl sales. The biggest genre for vinyl? Rock, with 68% of LP sales.

Tech Crunch:

…despite the rise of streaming, these services have not yet overtaken radio as the number one way people are discovering new music. Instead, 61 percent report hearing songs first on AM, FM or satellite radio; 45 percent say it’s word-of-mouth that leads to discovery; 31 percent hear songs in movies or in soundtracks; and then streaming clocks in at fourth place, with 27 percent saying they learned of new songs from streaming websites or apps…

In the U.S., consumers spend 24 hours per week on average listening to music. And of the 91 percent of Americans who listen to music, 75 percent report listening to music online every week, while 44 percent listen on smartphones…

Meanwhile, when it comes to spending on music, live music like concerts (32%) and music festivals (10%) still eat up nearly the majority of spend. Satellite radio accounts for another 11 percent of spending, while paid streaming registers at only 7 percent – behind physical sales (13%) and digital downloads (11%).

Posted in Misc | Tagged music streaming, Nielsen, video streaming | Leave a comment

Mobile App Usage Rose 58% in 2015

Posted on January 6, 2016 by GilPress

Mobile_growth

Flurry Insights:

In 2015 overall app usage grew by 58%. In this context, we define app usage as a user opening an app and recording what we call a “session.” With the exception of Games, every app category posted year-over-year growth with Personalization, News & Magazines and Productivity leading the way with triple-digit growth…. What was even more impressive is the majority of that growth rate came from existing users versus new users. In fact, in 2015, we estimate that 40% of the 58% total growth in sessions came from existing users, compared to 20% in 2014 and 10% in 2013…

Personalization apps saw their sessions balloon more than 332% in 2015. These apps range from Android lock-screens to Emoji keyboards. When we looked deeper into the category, we noticed that the majority of the growth is coming from Emoji apps (mainly keyboards) giving consumers the ability to share customized correspondence in their favorite messaging apps, such as Facebook Messenger, Whatsapp, Line and Snapchat. It is not a surprise then to see Kim Kardashian’s app “Kimoji”skyrocket to the number 1 spot on the Apple AppStore, on its launch day.

News and Magazine apps grew a whopping 135% in 2015. This growth validates the trend in media consumption we reported on last summer, signaling a shift in media consumption from television and PCs to smartphones in general, and phablets in particular, as we will discuss later.

Productivity apps continued the trend that started in 2014, with 125% sessions grow in 2015. In fact, more and more consumers, especially teens and college students are using their smartphones, phablets and tablets as their primary computing device and their sole device to access email and other productivity apps, like Google Docs, Quip, Slack and the Microsoft productivity suite.

Lastly, Lifestyle and Shopping apps grew 81% in 2015, following a 174% growth in 2014. This growth rate validates reports in early 2015 that mobile commerce is “growing like a weed” and already accounts for 33% of online commerce in the US and 40% of online commerce on a worldwide basis.

Inch by Inch, Mobile and its Apps Absorb the Media Industry.

Mobile_timeSpent

Time spent on phablets grew 334% year-over-year (2.9 times more than the average), compared to 117% for all form factors. With time spent on mobile surpassing that on television, and phablets posting astonishing growth in media consumption, it appears that the cable industry will find in the phablet and its apps its long-awaited digital nemesis.

The Phablet: The Unstoppable Media Consumption Device.

…In 2015, Flurry tracked a mind boggling 3.2 trillion sessions. When we started 8 years ago, we never thought that our counters could reach these numbers. But, we have been fortunate enough to have a front row seat watching the mobile revolution unfold and absorb (and in some case demolish) industry after industry.

Posted in Misc | Tagged Flurry | Leave a comment

History of Databases (Infographic)

Posted on January 4, 2016 by GilPress

Source: Cazena

Posted in Databases, Misc | Tagged cazena | Leave a comment

Technologies Shaping the Future: #cloud, #mobile, #IoT, #cognitive

Posted on December 29, 2015 by GilPress

technologies-of-the-future-cloud-mobile-tech

Source: World Economic Forum

Posted in Internet of Things, Misc, Predictions | Tagged technologies shaping the future | Leave a comment

Gartner, IDC and Forrester on the Future of Digital Transformation

Posted on December 27, 2015 by GilPress

digital transformation wordl

Gazing intensely into their respective crystal balls, Gartner, IDC, and Forrester have come up with predictions for 2016 and beyond, highlighting digital transformation and its impact on businesses and consumers worldwide.

According to Forrester, only 27% of today’s businesses have a coherent digital strategy that sets out how the firm will create customer value as a digital business. Gartner says, however, that 125,000 large organizations are launching digital business initiatives now and that CEOs expect their digital revenue to increase by more than 80% by 2020. IDC expects that the percentage of enterprises creating advanced digital transformation initiatives will more than double by 2020, from today’s 22% to almost 50%.

IDC predicts the emergence of the “DX (digital transformation) economy,” Gartner talks about the rise of the “algorithmic business” and the “programmable economy,” and Forrester charts a roadmap for companies responding to digitally savvy customers and consumers. Based on their predictions, here are 3 strategic trends and 3 sets of technologies – big data analytics, Internet of Things (IoT) and Artificial Intelligence (AI) – that will drive digital transformation for the balance of this decade.

Digital transformation will become the key strategic thrust for most CEOs

In 2016, CEOs will make a concerted effort to integrate the various digital initiatives across the business and create a clear digital vision that shows how the business will deliver revenue-generating digital experiences. B2B industries will start to close the digital gap with their B2C peers as they too are confronting rapidly rising customer expectations. By 2018, 67% of the CEOs of Global 2000 enterprises will have digital transformation at the center of their corporate strategy.

Digital transformation initiatives will be consolidated into one vision and function

In 2016, CEOs will make a concerted effort to integrate various digital initiatives across the business and create a clear digital vision that shows how the business will deliver revenue generating digital experiences. By 2017, 60% of enterprises with a digital transformation strategy will deem it too critical for any one functional area and create an independent corporate executive to oversee the implementation.

Digital transformation will require new skills and a shift in IT investments

By 2018, 35% of IT resources will be spent to support the creation of new digital revenue streams and by 2020 almost 50% of IT budgets will be tied to digital transformation initiatives.

Access to talent and the ability to hire the right people at the right time and place will become a big competitive differentiator. Enterprises pursuing digital transformation initiatives will more than double the size of their software development teams by 2018, focusing new hires almost entirely on digital initiatives. Digital skills like mobile app development, analytics, and design thinking will become the new normal for software development.

A greater reliance on digital will bring new challenges: The typical IT organization will spend up to 30% of its budget on risk, security and compliance by 2017, and will allocate 10% of IT staff to these functions.

Big data analytics will serve as the foundation of digital transformation

Embedded data analytics will provide U.S. enterprises $60+ billion in annual savings by 2020. While some enterprises will continue to drown in big data, others will use it to deliver personalized services, and will use emerging classification and analysis tools to find new insights in the data deluge.

Successful digital transformation will be based on establishing data streams in and out of the enterprise and finding new ways to monetize them. Data analytics will be embedded in all new apps, with a specific focus on automating actions based on real-time data analysis.

The Internet of Things (IoT) will be a catalyst for the expansion of digital transformation to all corners of the economy

Greatly expanding the range of digital interactions between consumers and enterprises and the scope and range of data creation, the Internet of Things (IoT) will serve as the growth engine of digital transformation.

By 2018, there will be 22 billion IoT devices installed, driving the development of over 200,000 new IoT apps and services. Also in 2018, six billion connected things will be requesting support and responding to service requests from things, creating new service businesses. In five years, 1 million new devices will come online every hour. IoT devices and solutions have the potential to redefine competitive advantage in every type of economic activity and fundamentally alter how consumers interact with enterprises and how enterprises interact with their supply chain and distribution partners.

Artificial Intelligence (AI) will drive new digital transformation revenue streams

Over the next few years, we will see a shift in focus for digital transformation initiatives from gathering and mining data to creating new models and algorithms that augment work activities and support consumers when they shop, trade, and make decisions.

By 2018, at least 20% of all workers will use automated assistance technologies to make decisions and more than 3 million workers worldwide will be supervised by a “robo-boss.” By 2020, autonomous software agents outside of human control will participate in 5% of all economic transactions.

Sources

Gartner

Gartner Says the Economics of Connections in Digital Business are Accelerating by the Use of Algorithms

Gartner Reveals Top Predictions for IT Organizations and Users for 2016 and Beyond

Gartner Says It’s Not Just About Big Data; It’s What You Do With It: Welcome to the Algorithmic Economy

Gartner Identifies the Top 10 Strategic Technology Trends for 2016

Forrester

Companies Will Thrive And Fail In The Age Of The Customer In 2016

Predictions 2016: The Trust Imperative For Customer Insights Pros

Predictions 2016: The New Breed Of CIO

IDC

IDC Predicts the Emergence of “the DX Economy” in a Critical Period of Widespread Digital Transformation and Massive Scale Up of 3rd Platform Technologies in Every Industry