Big Data News – 19 Jan 2016

Today's Infographic Link: The Illustrious Omnibus of Super Powers

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How do CIOs view their role within their organizations? Are they the chief innovation officers that they should be? A new study by IDC looks at how these executives see themselves and how others within their organizations view them.

At the Hadoop Summit 2015 in San Jose last summer, I had the opportunity to sit down with Tim Hall, VP of Product Management at Hortonworks to discuss his company's position in the Hadoop marketplace and what's in store for the newly public company.

There are no two ways about it. Adobe is killing it in marketing clouds. We know: We did the research at VB Insight, and we produce what is perhaps the most data-driven and comprehensive report on marketing clouds ever created. But success hasn't kept Adobe from adding to its marketing cloud offering. Today, at Retail's BIG Show, the National Retail Federation's 105th annual convention and expo, Adobe is introducing several additions to its marketing cloud and retail offerings. The one that stands out: Data-driven, history-aware remarketing. Within Adobe's marketing cloud, retailers can connect consumers' online behavior with contextual data to create (and send) a user-defined remarketing trigger.

We are moving to a future that is much like the birth of the PC market, far more focused on the needs and requirements of the users and the PC OEMs.

There is not much in the way of unified thought when it comes to storage, so the enterprise will have to do its best to define its own needs

AI and machine learning are graduating from science fiction to reality. It's estimated that about half of large enterprises are currently experimenting with AI projects. Several vendors, including Facebook, Google, IBM, and Microsoft, have donated machine learning development projects to open source.

VB EVENT: "Data" is a word so bland it seems to say nothing, but consider that pivotal scene in the old movie, Soylent Green, when the cry goes up: "Soylent Green is people!" Realizing that data represents people — individuals, with individual interests and needs — is the key behind Phil Bienert's controlled shift at GoDaddy from a focus on simple brand awareness to one that is personalization and data-driven, which is to say, people-driven. Phil Bienert, chief marketing officer at GoDaddy, will divulge the tools and tactics behind this kind of personalization at the upcoming Marketing.FWD Summit.

Europe's top antitrust authority is on the lookout for companies using big data to stifle competition, although it hasn't spotted any problems yet, according to Competition Commissioner Margrethe Vestager. It's good news when companies use data to cut costs and offer better service, the European Commission's competition chief said at the DLD conference in Munich on Sunday. "But if just a few companies control the data you need to satisfy customers and cut costs, that could give them the power to drive their rivals out of the market. And with less competition, there's a risk that there won't be enough incentive for companies to keep using big data to serve customers better," she said.

As data scientists are all the hype right now, many companies are hiring them without knowing how to best utilize their skills. This leads to a huge expense and a waste of resources. It's the classic "if it's not broke, don't fix it" mentality. Businesses need to know why–even if–they need a data scientist and know what they're looking to get out of the investment before bringing one on board.

News: Mass collection of data could be in breach of antitrust regulations.

Twitter is down: I feel for you. If you're in an affected part of the world, please stop mashing the reload button–maybe go outside for a few minutes? Alternatively, there's this thing called Google Plus. Perhaps you've heard of it. In IT Blogwatch, bloggers experience the five stages. Your humble blogwatcher curated these bloggy bits for your entertainment. [Developing story: Updated 2:55 am PT with more comment]

Twitter is down–sorry about that. So stop mashing the reload button, and go do something useful with your life for a few minutes. Alternatively, there's this thing called Facebook. You might have heard of it. In IT Blogwatch, bloggers experience five stages. Your humble blogwatcher curated these bloggy bits for your entertainment. Thanks for noticing. Chris Baraniuk notes the irony–Twitter network down for many users after technical fault:

Twitter was down, but it's gradually recovering–if you're still not seeing it, please stop mashing the reload button; maybe go outside for a minute? Or there's this other thing, called Google Plus. Who knows, you might like it. In IT Blogwatch, bloggers experience all five stages. Not to mention: The Ukraine Air Force do love an insane fly-by… Your humble blogwatcher curated these bloggy bits for your entertainment. [Developing story: Updated 2:55 am PT with more comment]

Reston, VA — January 16, 2016 — IKANOW, the leader in open-source information security analytics, today announced it has joined the ranks of the top 20 on Cybersecurity Ventures' Q1 2016 Cybersecurity 500 list at number 19. The Cybersecurity 500 is a directory of the most innovative cyber security companies to watch. "IKANOW's latest release is resonating with CISOs," said Steve Morgan, founder and CEO of Cybersecurity Ventures.

Big data is a statement that covers all information processing and gathering on a macro scale. With so much data flowing, a common thread is needed for actionable insights that are based on inputs. For online businesses, user behavior analytics and marketing are two sources of information, which trigger the need for taking action. Without efficient data optimization, there is poor use of money. It is due to the poor retention and lost conversations. Big data without action and insights becomes numbers without any real purpose. Most international online companies use big data to make improvements on customer, conversion marketing and website designs.

Spearphishing is a problem that's not going away and, in fact, tops the list of security concerns among enterprises, according to a Cloudmark study.

Facebook is opening an office focused on research for its Oculus virtual reality platform in Pittsburgh, of all places. An Oculus spokeswoman confirmed that the company has leased an office in Pittsburgh "that's dedicated to Oculus Research." In other words, it's not just for any employees of Facebook, and not just for any Oculus employees, either. Pittsburgh is an area where technology companies can find top-notch researchers.

Each year, major cyber security companies and other industry experts release their predictions for the year ahead. These predictions include what attacks they expect to see most frequently, as well as trends in security improvements. One of the threats that almost all of the experts believe will have a growing impact in 2016 is ransomware. What is it? What can you do if you are victimized? Better yet, how can you prevent becoming a target in the first place? Here are your answers. What Ransomware Is The beginning of a new year is an excellent time to review your security policies, data storage strategies, and online policies and procedures.

In this special guest feature, Manish Sood, CEO of Reltio, examines how business operations and data analytics can meet to obtain competitive advantage.

Traditional transportation models are converging around the development of smart cars–also known as cognitive vehicles–while new, disruptive technologies are coming to the forefront in various industries. But what are the possibilities when these different developments can be unified for the betterment of all?

Traditional transportation models are converging around the development of smart cars–also known as cognitive vehicles–while new, disruptive technologies are coming to the forefront in various industries. But what are the possibilities when these different developments can be unified for the betterment of all?

Fraud is a primary concern for financial institutions, particularly in the relatively porous channels opened by electronic banking and payments, which have seen notable exploitation by organized crime. However, some leading financial institutions have used emerging big data and analytics technologies to implement practical transformation plans that help them counter financial fraud.

Big data tools offer new opportunities to use real-time data to take timely actions that result in reduced cost, improved quality of care and more satisfied patients. However, the benefits are unevenly distributed across the physician community.

MapR Technologies, Inc., provider of the converged data platform that integrates the power of Hadoop and Spark with global event streaming, real-time database capabilities, and enterprise storage, announced that several MapR partners have integrated technologies with the MapR data platform and made them freely available for education, demonstration, and evaluation purposes via Amazon Web Services (AWS) Test Drive for Big Data.

Cablevision Argentina is using sophisticated IBM Analytics software to uncover the causes of customer dissatisfaction and proactively identify unhappy customers. As a result, the company can accurately target service improvements, boosting customer satisfaction and loyalty.

Did you know that athletes are not only monitored by cameras on stadiums, but also by many quirky devices such as accelerometers, heart rate sensors and even local GPS-like systems? Indeed, Big Data and modern technologies are currently revolutionizing sports and even powering the Fantasy Sports industry.

Along with social, mobile and cloud, analytics and associated data technologies have earned a place as one of the core disruptors of the digital age. 2015 saw big data initiatives moving from test to production and a strong push to leverage new data technologies to power business intelligence. As 2016 gets underway, five insiders share their predictions for what 2016 holds in store for the data and analytics space.

Driving is a risky form of transportation, as some 6.8 million car accidents happen every year, according to the National Highway Traffic Safety Administration. Technology that gives drivers automatic traffic updates could reduce that risk significantly.

Understanding the data in front of you is pivotal in not just understanding it but also planning and implementing it in the future. Data visualisation allows us to see trends, patterns and changes clearly and understand what changes to make. However, there are even more advantages and we're going to take a look at them in this piece.

The Definitive Guide to anything should be a helpful, informative road map to that topic, including visualizations, lessons learned, best practices, application areas, success stories, suggested reading, and more.  I don't know if all such "definitive guides" can meet all of those qualifications, but here are some that do a good job: The Field Guide to Data Science (big data analytics by Booz Allen Hamilton)

Data can fly beyond the bounds of our models and our expectations in surprising and interesting ways. When data fly in these ways, we often find new insights and new value about the people, products, and processes that our data sources are tracking. Here are 4 simple examples of surprises that can fly from our data: (1) Outliers — when data points are several standard deviations from the mean of your data distribution, these are traditional data outliers.




The late great baseball legend Yogi Berra was credited with saying this gem: "The future ain't what it used to be." In the context of big data analytics, I am now inclined to believe that Yogi was very insightful — his statement is an excellent description of Prescriptive Analytics. Prescriptive Analytics goes beyond Descriptive and Predictive Analytics in the maturity framework of analytics. "Descriptive" analytics delivers hindsight (telling you what did happen, by generating reports from your databases), and "predictive" delivers foresight (telling you what will happen, through machine learning algorithms).

It doesn't take a rocket scientist to understand the deep and dark connection between big money and big fraud. One need only look at black markets for drugs and other controlled and/or precious commodities. But what about cases where the commodity is soft, intangible, and practically virtual? I am talking about loyalty and rewards programs. A study by Colloquy (in 2011) estimated that the loyalty and rewards programs in the U.S. alone had an estimated outstanding value of $48 billion US dollars. This is "outstanding" value because it doesn't carry tangible benefit until the rewards or loyalty points are cashed in, redeemed, or otherwise exchanged for something that you can "take to the bank".

Open data repositories are fantastic for many reasons, including: (1) they provide a source of insight and transparency into the domains and organizations that are represented by the data sets; (2) they enable value creation across a variety of domains, using the data as the "fuel" for innovation, government transformation, new ideas, and new businesses; (3) they offer a rich variety of data sets for data scientists to sharpen their data mining, knowledge discovery, and machine learning modeling skills; (4) they allow many more eyes to look at the data and thereby to see things that might have been missed by the creators and original users of the data; and (5) they enable numerous "data for social good" activities (hackathons, citizen-focused innovations, public development efforts, and more). Some of the key players in efforts that use open data for social good include: DataKind, Bayes Impact, Booz-Allen Hamilton, Kaggle, Data Analysts for Social Good, and the Tableau Foundation. 

I recently had the pleasure of being interviewed by Manu Jeevan for his Big Data Made Simple blog.  He asked me several questions: How did you get into data science? What exactly is enterprise data science? How does Booz Allen Hamilton use data science?

A common phrase in SCM (Supply Chain Management) is Just-In-Time (JIT) inventory. JIT refers to a management strategy in which raw materials, products, or services are delivered to the right place, at the right time, as demand requires. This has always been an excellent business goal, but the power to excel at JIT inventory management is now improving dramatically with the increased use of data analytics across the supply chain.

One of the most important roles that we should be embracing right now is training the next-generation workforce in the art and science of data. Data Literacy is a fundamental literacy that should be imparted at the earliest levels of learning, and it should continue through all years of education. Education research has shown the value of using data in the classroom to teach any subject — so, I am not advocating the teaching of hard-core data science to children, but I definitely promote the use of data mining and data science applications in the teaching of other subjects (perhaps, in all subjects!).

In the world of big data analytics, there are several emerging standards for measuring Analytics Capability Maturity within organizations.  One of these has been presented in the TIBCO Analytics Maturity Journey — their six steps toward analytics maturity are:  Measure, Diagnose, Predict and Optimize, Operationalize, Automate, and Transform.  Another example is presented through the SAS Analytics Assessment, which evaluates business analytics readiness and capabilities in several areas. 

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