Big Data News – 13 Oct 2015

Top Stories
Dell's second annual Global Technology Adoption Index shows companies investing in big data, cloud, mobility and security are enjoying about 50% faster revenue growth than their competitors who didn't invest.

EverString, a leading provider of predictive analytics for sales and marketing, announced the release of EverString Predictive Ad Targeting, an ad targeting solution that is both account-based and fully integrated with predictive scoring and demand generation in a unified platform.

There are only two certainties in big data today: It won't look like yesterday's data infrastructure, and it'll be very, very fast. This latter trend is evident in the rise of Apache Spark and real-time analytics engines, but it's also clear from the parallel rise of real-time transactional databases (NoSQL). The former is all about lightning-fast data processing, while the latter takes care of equally fast data storage and updates.

Today Dell released a study which found that companies actively engaged in big data, cloud, mobile and security deployments are reporting up to 53 percent higher revenue growth rates than companies lagging in such investments and use. Here's why…

Graph databases aren't niche, argues Neo4j founder Emil Efrem. And they're hella fast. Matt Asay explains.

MapR takes JSON format data into Hadoop, while Teradata places its flagship database on AWS.

Organizations can now take advantage of the SAP Cloud Analytics service, codenamed Project Orca, which is available on demand.

Watson Analytics is not only revolutionary but also unlike any other analytics solution. At the event, which is called: Analytics for All: Empowering Everyone to Know, customers will share how they're improving their business with Watson Analytics.

Public utilities all over the globe are installing so-called "smart meters" that can take fine-grained snapshots of how resources like electricity, water, and natural gas are consumed in a given house or bulding. While the overall goals of these programs are noble–you can't conserve what you don't know you're consuming-the glut of usage data presents a major challenge to those tasked with analyzing it. There are many reasons to implement a smart meter, but some are better than others. For example, in drought-plagued California, homeowners recently discovered that smart water meters were helping water districts identify customers who were not complying with a statewide mandate to reduce water use by about 30 percent. That set off a firestorm of controversy that has yet to abate.

Guest blog post by Bill Vorhies Summary: Gartner drops "Big Data" from the Hype Cycle for Advanced Analytics and Data Science? What's going on? It is with heavy heart that I must relay to you that Gartner has dropped "Big Data" from its 2015 Hype Cycle for Advanced Analytics and Data Science. As recently as 2012 this category was called the "The Hype Cycle for Big Data", but alas, no more. RIP "Big Data". "Big Data" joins other trends dropped into obscurity this year including: decision management, autonomous vehicles, prediction markets, and in-memory analytics. Why are terms dropped?

The internet has been improved drastically since its origins of being used in university supercomputers to collaborate on research projects. It has revolutionised human behaviour – changing the way we communicate, conduct business, create and consume information. It has become very sophisticated and at the same time very convenient to use. Indeed many modern apps and conveniences rely on the internet without us often realising. The internet is a global computer network that is interlinked through URLs or a Uniform Resource Locator to access information stored on a different computer.

In the second episode of Big Data & Brews, live from Strata New York, Ovum principal analyst Tony Baer and I discuss recent announcements around big data in the cloud. Google, Amazon,…

At Amazon's recent re:Invent developer conference in Las Vegas, the company announced a new Internet of Things (IoT) platform called AWS IoT.

If you're trying to pull together consumer data collected in disparate sources but are struggling to make sense of it all, then you're long overdue for a strategy overhaul. At Insight 2015, learn how you can begin rethinking your own consumer data strategy.

I was recently asked a question by a customer that took me by surprise. Instead of asking what manual processes could be automated, this customer wanted to know which ones I would not recommend automating. I decided to take some time for this response as I didn't think it should be given lightly. After some…

Adobe is committed to making the cloud a seamless extension of almost any workflow process.

DataVisor, an innovator in utilizing Big Data analytics for Internet security, today announced it has secured $14.5 million in Series A funding, led by GSR and NEA, to help protect consumer-facing websites and mobile apps from cyber criminals.

In this special guest feature, Anand Shroff, CTO of Health Fidelity, discusses the challenges to using natural language processing in the hospital setting.

At its re:Invent conference, Amazon Web Services has unveiled two new instance types for its EC2 service: X1, sporting 2TB of memory, and T2.Nano, aimed to the lower end of compute requirements.

Know how to make the most out of BPM solutions

by Michele Usuelli Microsoft Data Scientist Azure Machine Learning Studio is a drag-and-drop tool to deploy data-driven solutions. It contains pre-built items including data preparation tools and…

The emerald isle is seeing significant numbers of startups basing themselves there

A Fateful Tale Ted is having a rough week at work. As a call-center employee, his main focus is on customer retention and offering promotions to his company's current subscribers. For some reason, his numbers are horrible this week. Not only are customers rejecting his promotions, they're actually canceling their subscriptions entirely! It's only Wednesday…

The aging of the global population presents an opportunity for the Internet of Things to transform an entire segment of healthcare. Learn more about how connected healthcare is poised to lead a wave of IoT-enabled business transformation.

Revolution R Open is a free, open source version of the R programming language and Revolution R Enterprise is an R engine for high-performance needs.

Many travel and hospitality companies are turning to data analytics to monetize customer satisfaction and drive greater customers. Businesses can use insights gleaned from big data analytics to provide personalized service, proactively address issues in real time and gain better understanding of customers.

VMware announced it will certify NFV modules that can run on top of its hybrid cloud computing platforms, among other announcements.

By empowering business to meet emerging governance, risk and compliance threats, next-generation GRC solutions–such as the IBM OpenPages GRC Platform–offer transformative business value, including predictive analytics and cognitive processing capabilities.

SAP is aiming to redefine analytics with a new software as a service (SaaS) offering that rolls up business intelligence (BI), planning and predictive analytics into a single service built on the SAP HANA Cloud Platform. "Really it's about simplifying access to a public cloud analytics experience that customers can trust," says Nic Smith, senior director of Marketing for Analytics at SAP. SAP plans to embed SAP Cloud for Analytics with existing SAP solutions that can connect to cloud as well on-premises data, giving organizations a single service that will provide employees with the capability to track performance, analyze trends, predict and collaborate to make informed decisions and improve business outcomes.

Apache Spark is exploding as a worldwide phenomenon since its origin in the Silicon Valley area of California. Find out just who widespread its adoption has grown in a survey of global examples, a wide array of community participations and upcoming event opportunities.

Today SAP made a big announcement. Over the past few weeks there have been hints here and there about Project Orca. Competitors have been speculating, and now, finally, the "killer whale" is in the ocean. I'm very happy to announce SAP Cloud for Analytics, a new generation of software-as-a-service (SaaS) that redefines analytics by providing…

Meteor has released Galaxy, its long anticipated cloud service for managing Meteor applications. In the blog post Announcing Meteor Galaxy, Matt DeBergalis says users "deploy Meteor apps into Galaxy with the same meteor deploy command you're already used to" and that it comes with the "day-to-day basics" including application logs and SSL cert management.

In part one, Leonid Ganeline introduced the concept of big memory and discussed why it is so hard to deal with in a .NET environment. In part two, Dmitriy Khmaladze describes their solution NFX Pile; a hybrid memory manager written in C# with 100% managed code.

Big data, everyone wants it, and most think they have it. But what you may have is simply a large quantity of data, not big data. Learn the difference and learn how to leverage both.

Unlocking New Potential With Topic Classification

By Vinnie Dessecker, senior consultant, big data — Strategy and Governance Center of Excellence There is an ever increasing need for businesses to engage in analytic innovation — exploring new, disparate and more data to gain insights to new products, services or other opportunities for an organization and its customers. Analytic innovation is really about seeing where the data takes you — determining in a scientific manner what actions can be predicted based on past performance. Much of the demand for analytic innovation is being driven by the era of big data — the availability of new data sources provides new and previously unimagined insights. So, what does it really mean to be innovative? What constitutes analytic R&D and how does this discovery capability relate to the other components of the data strategy? Innovation is synonymous with risk taking as an idea or hypothesis must, by definition…

Velocity is one of the defining characteristics of Big Data, and there are few situations in which speed is more imperative than motorsports. From NASCAR to Formula One and grassroots karting, teams and race organizers are employing ever more sophisticated data-driven strategies to shave split-seconds off lap times and provide a more thrilling spectacle for audiences.

Qualcomm arrived late to the ARM server party last week with its 24-core processor aimed at the server market. Lost in the hoopla, though, was a second bit of news that could be far more impactful. ARM servers have been far more hype than reality. For years there has been talk of ARM-based servers as an alternative to more power-hungry Intel Xeon servers. And the folks over at The Platform have noted, just days before the Qualcomm news, that we've been waiting a long time. So long, in fact, some early innovators have crashed and burned, most famously Calxeda. One of the first to produce an ARM processor for servers, it collapsed two years ago. HP's Redstone project made a big splash in 2011 but also has gone nowhere. Nvidia was working on its own ARM for the data center project called "Project Denver," but scrapped that in 2014.

Big data is having a big impact on just about everything these days, to the point where not including data analysis in business strategy is flat out neglectful. Check out how T-Mobile uses big data to increase bottom line.

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