Big Data News – 19 Oct 2015

Top Stories
Box is betting on developers to turn what began as a storage service into a content platform with its newly unveiled Box Platform.

We've heard a lot about how big data is changing the world, and even more about the changes that are still to come. There is more data collected now than at any other point in history, but many decision-makers have yet to figure out exactly what to do with all of this information. Thankfully, in… The post Five Wins for Retail with Predictive Analytics appeared first on Predictive Analytics Times.

SAP SE (NYSE: SAP) unveiled the SAP® Cloud for Analytics solution, a planned software as a service (SaaS) offering that aims to bring all analytics capabilities into one solution for an unparalleled user experience (UX).

The "data-driven enterprise" is becoming a reality as more and more executive teams look to support their decisions with data. Dashboards, such as the new products and services from Splunk and SAP, are on their way to becoming key components in the new executive reality.

As criminals adopt increasingly sophisticated approaches to fraud across all industries, counterfraud solutions must rise to meet the challenge. Attend IBM Insight to discover how you can protect your business by implementing advanced analytics and predictive analytics solutions.

The proliferation of computers in the daily operation of healthcare providers is generating unprecedented volumes of data. This volume will grow in size and complexity with the expected adoption of low-cost sensors. Some will be prescribe for research purposes, such as pediatricians monitoring asthmatics to find the environmental triggers behind their attacks. Others will be initiated by individuals outfitting themselves with a raft of consumer electronics that measure such signs as heart rate and blood pressure. Buried in the resulting databases may be answers to how to improve patient outcomes and hold down the cost of healthcare. It's a great example of how Big Data can be put to good use.

Incumbents IBM, Microsoft, Oracle, and SAP have ruled the Gartner Magic Quadrant for operational database management systems for years. But with the rise of open source and cloud, new competition has gained ground. Here's what you need to know.

Lab test market leader Quest Diagnostics recently announced an important big data analytics partnership with Inovalon, a cloud-based analytics provider, to deliver real-time patient analytics to Quest's vast community of physicians and hospital systems. The partnership is a crucial step in Quest's evolution from a company known only for lab tests to becoming essentially a health information services company. This is important at many levels for healthcare industry observers, and more specifically, for healthcare CIO's.

As healthcare providers collect more data on patients than ever, and plan to use to predict care episodes, healthcare need to understand the ethical implications, according to experts speaking at the Predictive Analytics World Healthcare conference in Boston Tuesday. Right now, the lines are blurry. "We had a case we saved someone's life by looking…

My predictions are a little early this year, but don't worry, they're of the same sterling quality you've come to expect. Most apply to big data, but I've stepped outside the confines of my usual domain here and there for your entertainment. Enjoy. Developer trend No. 1: Containers will rule the world Docker will continue to develop, gain security features, and add various forms of governance so that you are unable to pull down a tree of containers that depend on pnwd.com. Emulating an entire machine on top of a machine was fundamentally a wasteful idea. Solaris zones were a good idea; Solaris zones on Linux with a packaging format are an even better idea. Add dependencies, and you're on fire.

Every organisation is different and there's no one-size-fits-all Cloud solution. Talking it over with a consultant can be a great help in understanding all the pros and cons of different cloud infrastructures and services.

2014 and 2015 have seen a slew of significant M&A deals in the Big Data/NoSQL/BI/Analytics space. Let's analyze the done deals so we can plan for what's to come.

Advanced Analytics is Needed to Bring Insight & Value to Big Data

Today's software applications have a lot of concurrent tasks that are distributed over multiple threads, processes, processors and PCs. This article introduces a visual modeling technique to describe and specify the application's execution architecture. Within Philips Healthcare the Unified Execution Diagram has proven to be very useful for designing and documenting the execution architecture.

Dominica DeGrandis talks about bringing visibility to the workflow, reducing cycle time, setting priorities right, what is real firefighting, and how Kanban and DevOps are the perfect marriage.

Belinda Waldock is an agile business coach and a professionally qualified Institute of Leadership and Management (ILM) coach and mentor. She has drawn on her experience coaching and mentoring organisations in the implementation of agile approaches inside and outside of information technology and written the book "Being Agile in Business". She spoke to InfoQ about the book

Peter Bell discusses how to identify the ideal job and build a personal brand that'll make you the obvious choice for the gig. Peter also addresses balancing management and coding as well as how to think about freelance vs. full time and startup vs enterprise opportunities. By Peter Bell

Jessica Kerr covers some of the concurrency tools existing in JVM languages including ExecutorService, Futures, Akka actors, and core.async coroutines, providing advice on writing deadlock-free code. By Jessica Kerr

Bas Vodde and Craig Larman framed and introduced Large Scale Scrum (LeSS), the scaling model. Large-Scale Scrum (LeSS) is Scrum applied to many teams working together on one product. InfoQ interviewed Bas Vodde to discuss more about LeSS framework.

Georgi Knox conducts a hands on session overviewing the history of Linux, what the kernel is, what system calls are, how to write modules, how to build a kernel, etc. By Georgi Knox

Bob Familiar introduces microservices, discussing their architecture and outlining cloud deployment scenarios, exemplified by a live demo on Microsoft Azure.

Noopur Gupta shows how to get started with Java 8 in Eclipse, demonstrating how the new Java 8 constructs blend with the existing functionality in Eclipse.

Neutrinos, the so-called ghost particles, are notoriously difficult to detect. Billions of them generated by the Sun pass through your body every second — and at night, that's after passing through the entire Earth — and you never notice, because they hardly every interact with anything. Their antimatter cousin, the antineutrino, is similarly ghostly but just a little easier to detect … as long as you have a detector the size of an office building buried a mile underground to shield it from cosmic rays (which would drown out the antineutrino signal with false positives). That's what a team of geophysicists led by the National Geospatial-Intelligence Agency did: in fact, they built two dectors and combined with data from 400 nuclear power plants around the world to make a map of natural and man-made radioactivity (which generates antineutrinos). The map below shows intensity of natural sources (particularly in central China) combined with pinpoints of manmade generation at nuclear sites. The nuclear power network in Europe is particularly clear. 

Tim Reid, an innovation consultant and a comedy writer, shares the tricks of the trade that help comedy professionals stay fresh and original and shows how all can become as creative as comedians.

One of the widely held misconceptions in the field of big data analytics is that you can scale your way into insights by just adding more data. That may be true in some situations, but as 538 Editor in Chief Nate Silver and Crowdflower CEO Lukas Biewald said at this week's inaugural Rich Data Summit, it's just not that simple. Silver led off his keynote address at Wednesday's Rich Data Summit with a reference to the 2008 story "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete," written by Wired magazine editor Chris Anderson. Silver, the statistician and former baseball analyst who wrote the 2012 book "The Signal and the Noise," had good things to say about Anderson in general, but not this particular story.

Irina Guberman discusses maximizing throughput on multicore systems with Erlang and the Jobs framework by Ulf Wiger.

The barriers to collecting and analyzing log and sensor data are lower than ever, and businesses are starting to capitalize on the emergence of the industrial IoT.

With trading speeds calculated in milliseconds, the need for accuracy and compliance in data tracking among high-frequency trading firms has become a Darwinian race for perfection. The stakes are not just to eliminate the billions of reporting errors or capture the billions in annual profits, but also to simply survive.

Dave Haase cycled 3,000 miles during the 2015 Race Across America, all while using IBM Analytics to monitor heart rate, distance ridden and power output. What can businesses learn from Dave's extraordinary feat of endurance?

Dataiku's DSS 2.1 has a wide variety of new features including better graphs, code snippets, and plugins   New York City, NY: Dataiku (www.dataiku.com), a software developer firm, has released the latest version of Data Science Studio (DSS), a software platform that combines all of the steps and big data tools necessary to build highly specific services that turn raw data into impactful business solutions. DSS 2.1 has an array of brand new features and with so much cool new stuff, there is no need to be modest.     Better Graphs and Charts   One of the first improvements is DSS's Charts module. The entire visual interface has been redesigned to make it easier for users to get the precise data visualization they want. Users will find a greater number of new charts, therefore enabling them to visualize data and analysis results in the most comprehensive ways.

My predictions are a little early this year, but don't worry, they're of the same sterling quality you've come to expect. Most apply to big data, but I've stepped outside the confines of my usual domain here and there for your entertainment. Enjoy. (Insider Story)

Hello DSC Member, Join this webinar to hear Tinder VP of Technology Dan Gould discuss how Tinder re-invented its behavioral analytics approach with Interana to tune matchmaking and business operations. ESG Senior Analyst Nik Rouda will discuss the broader benefits of behavioral analytics on event data with best practices and industry research. The webinar will cover topics such as: Why a solution built for speed and scale (trillions of events in seconds) is so important to Tinder and the insights it's enabling. How Tinder uses behavioral analytics to understand their users to improve features and develop new ones such as Super Like.

In this eMag, you'll find practical advice from leading practitioners in cloud. Discover new ideas and considerations for planning out workload migrations.

Today, the Internet of Things (IoT) is creating new challenges and opportunities for the automotive industry. However, applying analytics to this tide of IoT data can help turn it into competitive advantage.

If you work with both Matlab and R, the R.matlab package maintained by Henrik Bengtsson on CRAN helps you to connect the two environments by allowing you to read and write Matlab's MAT data file format from R (even if you don't have Matlab installed). This allows you to pass data between Matlab and R via the filesystem. But if you want to build an integrated R/Matlab workflow, and call Matlab functions directly from R, there is also the reach package by Christoph Schmidt (available on Github). The reach package works with a Matlab installation behind the scenes, by writing scripts for batch execution by Matlab, and exchanging data via files.

SOLVING SCARCITY THROUGH WATER REUSE: DATA SCIENCE INNOVATION CHALLENGE GE understands solving the world's toughest problems through advanced manufacturing techniques and processes requires collaboration. By crowdsourcing innovation–both internally and externally–GE is improving customer value and driving advancements across industries. By sourcing and supporting innovative ideas, wherever they might come from, and applying GE's scale and expertise, GE's approach to open innovation is helping to address customer needs more efficiently and effectively.

How do brick-and-mortar stores compete with online retailers? Stores can tap big data to track customer movement and enhance the shopper experience.

The insights organizations derive from data have the potential to transform the way entire industries do business. But to realize that potential, industries need to be able to focus their efforts, both on the problems they want to solve and on the data analytics best suited to the task.

Healthcare professionals can provide personalized care by analyzing the each patient's data. This includes mHealth data, risk calculators, drug summaries and health records.

Samsung SAMI is a Data-driven Development (D3) platform for receiving, storing and sending data to/from IoT devices. Any device can send data in various formats which is then normalized into a JSON format and stored in the cloud. Data can then be requested by other devices.

Digital banking is making greater inroads with customers, so how can established banks fight this competition? By streamlining processes, getting rid of paper and becoming more customer-centric. This transformation enables institutions to become more agile, responsive and personalized.

SAS Enterprise Miner helps users develop descriptive and predictive models, including components for predictive modeling and in-database scoring.




GoodData has added distribution capabilities to its platform that allow for granular control over how data is pushed out to application users.

There's no tricks, but only treats at Insight 2015. From Spark to the IBM Analytics Platform, find out why you won't want to be anywhere else this October.

The banking and financial services industries are very data-centric as every interaction that a client or partner system has with a banking institution produces actionable data that has potential business value associated with it. Big Data technology (led by Hadoop) is changing the landscape in areas as diverse as Risk Management, AML Compliance, Fraud Detection, Cyber Security and Customer Analytics. In this webinar series, we will explore some of these global themes and discuss specific use cases & business areas that are leveraging Big Data across the world largest global financial services organisations. The post Big Data in the Financial Services Industry appeared first on Hortonworks.

In this special guest feature for our Data Science 101 channel, Smita Adhikary of Big Data Analytics Hires highlights how data scientists sometimes tend to get bogged down in the "how" of a problem rather than the "why" of it, and end up delivering highly predictive, yet essentially meaningless models for the business.

In this special guest feature, Marty Loughlin of Cambridge Semantics Inc. talks about new tools that are making it possible for anyone in the enterprise to intuitively "surf" information found in data lakes without specialized analytics skills, setting the stage for big data analysis to be as common as spreadsheets.

Mobile marketing efficiency is unthinkable without qualitative mobile analytics for both apps and ads. This post reviews two of the most popular mobile analytics services and provides some additional insights about using mobile analytics.

It is an exciting time to work for a utility company. The electric grid and utility sector is undergoing the most massive change since Thomas Edison invented the light bulb in 1879. It's safe to say that the technology innovation occurring in the electric grid over the next decade will likely dwarf many of the changes that occurred during the previous century.

Big data is commonly associated with "The Three Vs," specifically volume, velocity, and variety. Although big data is often considered to be the domain of data scientists, these three characteristics are near and dear to the heart of market researchers.

Larry Maccherone is a researcher who has focused on collecting and presenting real metrics for agile teams and using analytics to help teams get better at forecasting in uncertain environments. He recently joined AgileCraft as their Director of Analytics – he discussed the move, how AgileCraft is designed to gather data from many ALM tools and how analytics can be used effectively.

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