Big Data News – 15 Aug 2016

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Analytics software and consulting provider Palantir has acquired Silk, a data visualization startup. Silk's platform will continue to operate unsupported as the company's team will join Palantir.

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Take a moment and think about the most important day in your business. Was it your launch day? The day you revealed a new product? The day your manufacturing line got a new machine? The day that you closed a huge new account? What would happen if, during your biggest day of your business, your IT systems completely failed you?

Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

In this special guest feature, Guy Levy-Yurista, Ph.D., Head of Product at Sisense, discusses the increasing shift in BI and data analytics towards self-service solutions.

Machine learning is technology which trains software so developers don't have to code it by hand. The number of new companies in the category has grown exponentially over the past few years. Here are 10 machine learning startups worth a closer look.

Our roundup of intriguing new products from companies such as Kaspersky Lab and Untangle

Due to the success of our MSc program in 2015/16 we will be increasing sponsorship for up to 90 Masters students

Omega World Travel turns to advanced analytics to deliver dashboards that provide views of critical metrics and push out the data to smartphones and apps.

Sometimes it is just obvious that an organization has a high Customer IQ.  I once experienced it from an electronics manufacturer.  My LCD TV was starting to break down — there were horizontal lines…

Argyle Data, a leader in big data/machine learning analytics for mobile providers, has highlighted the role of supervised and unsupervised machine learning in detecting and preventing anomalous mobile traffic.

Apple, Intel, Palantir, and HPE were among the tech giants acquiring data analytics and machine learning companies. Here's your Big Data Roundup for the week ending August 14, 2016

Digital Transformation is inevitable. Across all industries, from consumer goods to health care, manufacturing to financial services, companies are going digital. Digital technologies from social…

More and more business owners are moving their IT infrastructure to the cloud. The benefits are numerous: reduced It costs, reduced energy consumption, better efficiency in collaboration, scalability, and automatic updates. But maintaining the security of valuable business and client data is still paramount to avoiding data loss or compromise. PrecautionsBusiness owners should consider the following before adopting cloud services in their company:

Nimbix, a leading HPC cloud platform provider, announced a significant increase in their presence in the machine learning market space as more customers are using their JARVICE platform to help address the need for an easier, more cost efficient way of working with machine learning.

Okay, okay, that seems like an odd thing to say. But at a recent keynote, that came out of my mouth. But that's a confusing statement, so let me share the entirety of what I said: Big Data is about getting small; it's about getting down to the level of the individual. Sometimes the Big Data conversation gets too fixated on the "big" part of the conversation: Is my data big enough? Is my company big enough? Is my analytics team big enough?

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week. Announcement Predictive Analytics World for Financial Services explores predictive analytics usage by banks, insurance companies, credit card companies, investment firms, and other financial institutions.

Did you heard about the AWS IoT button? Anyone who has basic programming skills can easily test out different IoT applications and create their own through the IoT button. Create the AWS IoT resources, configure your button and count items, call/text someone, start/stop a process, etc.

This contributed article takes a deep dive into how big data can transform your work environment through things like: data-driven decision-making and being able to identify high and low performing employees, and how low level employees will now be able to develop a voice when solving problems for upper-level management

Discover why big data and the Internet of Things are proving to be so effective in the food industry, and what other industries can learn from these use cases.

Get the most value from your company's data now and in the future by following these three steps to incorporating curation into your big data strategy.

A little over two years ago, I wrote about the ongoing cloud wars with all of the 800lb gorillas in the room jockeying for position. At the time, IBM and Amazon were having what equated to a public cage match battle over a cloud contract with the CIA (IBM Steps back from CIA deal) as well as various ad blitzes, including IBM running ads on buses in Las Vegas during Amazon's premier re:Invent conference.

"It is not necessary to change. Survival is not mandatory." — W. Edwards Deming. How often do we see this quote used in DevOps blogs without a hint of irony? It's as if we need to instantly complete generations of evolution to stave off extinction, like trying to grow an extra lung overnight. DevOps or Die!!! So this is it — the dreaded DevOps transformation looms large. The department will be 'shaken up', practices will be 'turned on their head', and staff will be 'taken out of their comfort zone'. It's sink or swim: The extinct will be carried out on stretchers, to graveyards in which Ops and Dev are siloed for eternity.

A squirrel through a GoPro Camera was a nut, and grabbed it and took it up a tree, providing a squirrel's eye view of the branch-based highways of squirrel-land (via Gizmodo): Keep an eye out for…

It's difficult enough for marketers to stay on top of the latest data about consumers, but reaching the right people in the B2B world presents a whole host of new challenges.  On Friday, Oracle unveiled what it calls the largest marketplace of audience data targeted specifically at brands that sell to other businesses using programmatic and data-driven B2B marketing techniques.

A very wise man in a movie once put it, "It's good for a man to know his limitations." When it comes to a computer system, it's essential. Understanding your capacity is a healthy part of running a business. Any business must understand what it needs in terms of its personnel (and the resources to support those personnel) to support and sustain itself. A technology business must take this understanding further in terms of its networking, hardware, and software infrastructure.

Originally posted on Data Science Central The era of big data has witnessed a paradigm shift into analytics. Today, it's no longer sufficient to simply gather data from social media, IoT, and wearable devices, and be unable to manage or filter it. It is more about delivering the right data to the right person, at the right time. This trend is growing crucial as data is multiplying every day and pouring in from various devices and smart machines including wearables, electronic gadgets, and other devices. Such factors call for the treatment of vast pools of structured and unstructured data with care and precision.

Google Fiber moving toward wireless, the Quadrooter Android flaw, good news for SD-WANs, and easier equipment installations in historic buildings.

My colleagues Max Kaznady, Jason Zhang, Arijit Tarafdar and Miguel Fierro recently posted a really useful guide with lots of tips to speed up prototyping models with Microsoft R Server on Apache…

This post lays out some helpful advice for organizing and running an R demo at your organization. Seeing is believing so its best to demo the power of R yourself. Check out this post to get you started. Have more tips? I'd love to hear them! 1) Pitch them R You know R is amazing and now it's time to convince your team. Start with the basics – R is a powerful, open-source statistical programming language that can be used to gather, manipulate and visualize data. 

Although vendor-written, this contributed piece does not promote a product or service and has been edited and approved by Network World editors. Finding a cloud provider you can trust has become a major responsibility.  

Program Chair, Predictive Analytics World for Government In anticipation of his upcoming conference keynote presentation, Implementing Predictive Analytics at CMS: Lessons Learned and Future Directions at Predictive Analytics World for Government, October 17-20, 2016, we asked Dr. Shantanu Agrawal, Deputy Administrator for Program Integrity and Director of the Center for Program Integrity at the Centers for Medicare & Medicaid Services (CMS), a few questions about his work in predictive analytics. Q: How would you characterize your agency’s current and/or planned use of predictive analytics?

This vendor-written tech primer has been edited by Network World to eliminate product promotion, but readers should note it will likely favor the submitter's approach.

Hewlett Packard Enterprise has acquired another high performance computing company with a long history in Silicon Valley — SGI — in a deal worth $275 million. Here's what the acquisition indicates about HPE's strategy going forward.

Organizations must confront a number of thorny issues regarding what to put on the cloud, how to do it, and what type of cloud is warranted.

1010data, Inc., the only integrated platform that combines self-service data management and analytics at scale with ready-to-use data, announced enhancements to its popular Consumer Insights Platform (CIP) with the release of CIP 3.0.

My friend Dan sent me this press release (since he knows that I like all things "Data Analytics" related). In the press release, "Boeing Announces Data Analytics Agreements with Six Airlines," Boeing announces that they are providing advanced analytic solutions to several airline customers including: All Nippon Airways (ANA) signed a renewal contract for Airplane Health Management (AHM) on its entire future fleet of Boeing 787 aircraft. ANA uses AHM tools to monitor their aircraft in real time and proactively manage maintenance operations more efficiently.

While API virtualization is already over a decade old, many developers, testers, and decision-makers still misunderstand it. Virtual APIs create an environment that teams can use to mimic the characteristics of the production environment and create simulated responses from all APIs the application relies on. API virtualization is a single technique that pays off in several distinct roles. Let's take a look at a few examples to help illustrate the benefits attached to virtual APIs.

Q&A: CBR talks to Magnitogorsk Iron and Steel Works about their deployment of Yandex Data Factory technology.

Analysis of variance is a method used to evaluate differences between the two or more groups.  It works by breaking down the total variance of the system into the between group variance and within group variance.  We discuss this method in the context of wait times getting coffee at Starbucks.

Database vendors are looking for new memory technology options as datasets continue to soar. With that in mind, Redis Labs Inc. claimed this week that its database running on flash memory along with Intel Corp.'s NVM Express flash-based SSDs achieved record performance. Redis Labs, Mountain View, Calif., announced Thursday (Aug. 11) during the AWS Summit in New York City that the combination of flash memory and Intel's NVMe flash drives yielded a benchmarked throughput of 3 million database operations per second at under 1 millisecond of latency.

Most of these infographics are tutorials covering various topics in big data, machine learning, visualization, data science, Hadoop, R or Python, typically intended for beginners.

Social media enables the businesses to interact with fans and prospects at real time. It also generates publicity and increases brand awareness. In today's world of digitisation, almost everyone is available on social media. Hence, social media marketing is really advantageous for small business owners  whose brands are not so popular.

IBM Watson and Columbus Collaboratory recently partnered on CognizeR, an open-source R extension that lets data scientists using R more easily use Watson tools.

In anticipation of her upcoming conference presentation, Predictive Analytics for Different Business Types:  Optimize All the Funnels, at Predictive Analytics World New York, October 23-27, 2016, we asked Meina Zhou, Data Scientist at Bitly, a few questions about her work in predictive analytics. Q: In your work with predictive analytics, what behavior or outcome do your…

Parse is the Facebook's Mobile Backend as a Service provider that application developers use for web or mobile apps. It allows you to develop the app without worrying about creating your own backend. The reason developers like Parse is because it offers many ready-made features that can easily be customized. Some of these includes:

It's surprisingly difficult to find a concise proper definition of just what exactly DevOps entails. However, I did come across this quote that seems to do a decent job, "DevOps is a culture, movement or practice that emphasizes the collaboration and communication of both software developers and other information-technology (IT) professionals while automating the process of software delivery and infrastructure changes."

Work at home! Make millions online! Big data analysis shows that 2016 is the most junk mail-ridden election of all time, and "get rich like Trump" tops the spam charts.

Through mining consumer blogs, social media posts, and file downloads, streaming companies and producers learn what themes, writers and actors they need to combine in order to maximize their chances of success.

As we know, a customer usually goes through a path/sequence of different channels/touchpoints before a purchase in e-commerce or conversion in other areas. In Google Analytics we can find some touchpoints more likely to assist to conversion than others that more likely to be last-click touchpoint. As most of the channels are paid for (in terms of money or time spent), it is vital to have an algorithm for distributing conversions and the value between those channels and compare with their costs instead of crediting e.g. last non-direct channel only.

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