Big Data News – 26 Sep 2016

Today's Infographic Link: Winter Storms

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Assessing the voting public’s mood swings, likes and dislikes in order to win an election has been a top-line task for political campaigns in the U.S. for most of its 240 years of existence. But only in the last decade have the internet, social networks and real-time analysis of big data collected from all corners of the country played a central role in helping sway voters to determine the leader of the nation and of the Free World.

Top Stories
Inhi Cho Suh shares more of her vision for IBM and the tech realm in general.

The number of user accounts affected by Yahoo's security breach — previously reported as 200 million — turns out to be more like 500 million.

CA Technologies has announced it is in the process of acquiring BlazeMeter.

Looking for a unicorn? Get in line. Actual data scientists are in high demand, and there's not enough of them to go around. If you want identify the right talent, consider these tips.

During an intense U.S. presidential campaign, millions of people are chatting about the election every day on Twitter. MIT is studying them. More precisely, the Laboratory for Social Machines, part of the MIT Media Lab, has launched a project called the Electome that charts Twitter in unique detail. Now the project has joined forces with the Commission on Presidential Debates — the first debate is tonight — to provide journalists with a "dashboard" summarizing Twitter use during the debates. MIT News talked to three key Electome researchers about their work: Deb Roy, director of the Laboratory for Social Machines and chief media scientist for Twitter; William Powers, long-time journalist, author, and now research scientist for the Electome project; and Russell Stevens, deployment lead for the Electome project. This interview has been edited for length. Q: What is the Electome and how does it work?

By and large, this blog is for my own amusement. Anyone reading it, is a member of an exclusive club. Yet, it may have made a difference.  secure.ssa.gov was not secure on Sept. 4, 2016 I recently wrote that the secure section of ssa.gov, the website of the US Social Security Administration, was not secure. As shown above, it was rated C, a really bad grade, at the SSL Server Test run by SSL Labs. 

What about DevOps? Where are all of those guys hanging out? While there may not be one clear and specific hangout place online for the entire DevOps community to gather, here is a list that can help you connect and hear from educated DevOps professionals who can provide you with information about everything DevOps related that you need to know.

This Hub presentation details 4 of the most common challenges organizations face when managing incentive compensation.

Under mounting pressure to meet the January 2019 deadline for FRTB implementation, banks must persuade regulators that they have adequate capital reserves and have implemented a stress-proof risk framework. However, a survey of 100 banks conducted by Chartis Research indicates that many banks may be largely unprepared to meet this challenge. In this podcast, explore the business impacts of FRTB while learning how banks can achieve compliance through resource and budget allocations, technology implementation and the like.

An ordinance helps Google Fiber, Cisco makes a deal with Salesforce and the OpenDaylight Project has introduced Boron.

Strategy Extends Beyond Technology Adoption and Fosters Use Case Exploration, Discovery and Best Practices SAN FRANCISCO, Calif., Sept. 21, 2016 — As an extension of its end-to-end, modern business intelligence (BI) platform, Datameer today introduced a series of tools designed to help companies discover and implement long-term data analytics strategies and best practices. Recognizing that the big data market is maturing and companies need value-based outcomes, Datameer is bucking the status quo and going beyond technology implementation to provide customers with a blueprint to success. Gartner predicts that, through 2017, 60 percent of big data projects will fail to go beyond piloting and experimentation, and will be abandoned. As a pioneer in data analytics, Datameer has already helped hundreds of customers be successful with their big data journey and is leveraging that knowledge to develop a roadmap that identifies relevant use cases, aligns teams and establishes a mature big data analytics model that can be operationalized. Use Case Exploration The single greatest risk for big data projects is a lack of high-value business use cases. Datameer's new Use Case Browser allows stakeholders to explore hundreds of real-world big data use cases to better understand the business and technical components. Based on either industry or data sources, the browser lowers the barrier for users to ascertain, concretely, how data analytics can impact their bottom line. Use Case Discovery Going one step further, Datameer is now offering a more immersive experience through its Use Case Discovery Workshop that teaches business users and teams how to clearly identify and define a set of relevant business use cases. The half-day event will focus on team alignment across lines of business, analytics and IT and employs a unique process that helps attendees: Discover — the workshop uses a unique gamification approach to group-based discovery to identify the key use cases and align the teams on those. Define — the session will help define the key personas for the use cases and the critical barriers to implementation.

Reading up online is a valuable tool for keeping pace with developments in data science — if it wasn't, there wouldn't be so many email lists on the topic. But there's also no real substitute for in-person learning. Reading a case study doesn't compare to hearing from its writer and being able to delve deeper with questions. Webinars aren't the same as live walkthroughs. And networking is more personal with handshakes instead of thumbnails. That's why people keep coming back to Predictive Analytics World. Next month, Predictive Analytics World comes to New York, and there are still seats left at this exclusive event. Data Science Central readers save an extra $150 with code DSC150. Book now and see for yourself what people are talking about. PAW Business New York is co-located with PAW Healthcare, PAW Financial, and the eMetrics Summit.




Creating the SDDC will be no walk in the park, but working in one should be a snap compared to today's complex infrastructure.

Whaling is a type of spearphishing targeting "big fish" in an organization with access to sensitive, highly-valuable information.

The F1 score is a model diagnostic that combines precision and recall to provide a singular evaluation for model comparison.  In this episode we discuss how it applies to selecting an interior designer.

Slides have now been posted for many of the talks given at the recent Effective Applications of the R Language (London) conference, and I thought I'd highlight a few that featured Microsoft R. Chris Cole manages the deployment of R at Investec, supporting investment and risk teams worldwide. Despite some initial grumbling about having to use "old" versions of software, the R developers ultimately appreciated the improvements in collaboration and IT support derived from a standardized "R Suite" company-wide.   Investec also supports R deployment for other analysts who don't necessarily use R, by integrating R into desktop applications via a centralized DeployR server. This provides managed R-based analytics throughout the company, without the need to manage R on individual desktops. Adam Rich has been evaluating the in-database capabilities of SQL Server 2016 R Services for Beazley Group. In his presentation, he compared and benchmarked various architectures and processes for applying R to data in SQL Server. The results varied by the type of load applied (calculating a mean of 60,000 rows vs 6,000,000 rows); pulling data from SQL to R was faster for the small loads, but pushing R code to the database was better for heavy loads. Ben Downe, head of business intelligence at British Car Auctions, deploys R models developed in-house to the production environment using Azure ML. He describes the benefits of using the "one button API" to publish R functions as a Web service as "simple creation and destruction of new containers for new models / new test versions", "doesn't need to use IT resources", and "value for money". He also described using the Custom R Modules feature of Azure ML to simplify the process of updating R functions in deployment. You can also check out the slides from my own keynote presentation, The R Ecosystem. There, I suggest why R is such a popular language despite being a language designed for data science (rather than a general purpose language), and having some idiosyncratic features (which seem quirky to some programmers, but make it easier to use for those with a background in data science).

Teradata is not the first platform company to aim higher up the value chain towards a solutions business. The journey will be a balancing act for avoiding conflict with the analytics software partners that have been pillars of its ecosystem.

Introduction to Hortonworks DataFlow Learn about Hortonworks DataFlow (HDF™)and how you can easily augment your existing data systems – Hadoop and otherwise.  Learn what Dataflow is all about and how Apache NiFi, MiNiFi, Kafka and Storm work together for streaming analytics. Join us:  Oct 6, 2016, 10 am PST Make Your Big Data Ecosystem Work… The post How to Harness the Power of Data-in Motion: Webinar Series appeared first on Hortonworks.

Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata's revenues are down about 5 percent, which likely prompted some changes at the company. Over the past few years, Teradata made several technology acquisitions and perhaps spread its resources too thin.

As a startup, it's important to make smart investments with your capital in order to maximize the return and have the most possible business impact. Well-funded startups can sometimes spend money in the wrong areas. Here are our best tips on where startups should invest their money when it comes to business technology:

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