Big Data News – 23 Sep 2016

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Median base annual salary for IT workers was flat this year, according to the results of the InformationWeek 2016 US IT Salary Survey. Still, certain roles — including architect, project leader, and security specialist — are commanding much higher median salaries than other roles. See if you're in one of the 10 best-paying IT staff positions — and how your total compensation stacks up.

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IT pros and developers looking for new opportunities and new grads looking for an advantage in getting that first IT job are exploring new education options — IT and technology education boot camps. In this InformationWeek Expert Voice podcast, we spoke with a provider of these intensive sessions about what they are and why they are becoming popular now.

Big data firm Datameer analyzed thousands of tweets in the week preceding the debate, revealing that the two candidates have never been more controversial-or unpopular.

Technology has considerable potential to make the world better, but those benefits are far from guaranteed. Plenty of downsides can pop up along the way, and some of them have Turing Award winners especially worried. 1. The internet echo chamber "Technology by itself is not evil, but people can use it for bad things," Barbara Liskov, an Institute Professor at MIT, told an audience of journalists Thursday at the Heidelberg Laureate Forum in Germany. "I do worry a lot about what's going on." The ability to selectively filter out news and opinions that don't agree with one's own viewpoint is one of Liskov's top concerns.

Dell wants to prove that you don't need a high-end GPU in your computer to create content for virtual reality headsets. Instead, the company wants to move VR content creation into the cloud with new computing products it plans to release. The goal is to add more mobility and security to VR content creation. Among the new products planned are thin clients that run applications stored in remote servers or appliances. The servers will have GPUs that power VR content creation on  virtual desktops. Virtual reality is an interesting market, and Dell will have products to talk about in the future, said Jeff McNaught, executive director of cloud client computing at Dell.

In Lew Cirne's view, all companies are now software companies and understanding how your software is treating your customers is key to business success. Cirne is the founder and CEO of New Relic, a cloud-based provider of application management tools. In this CEO Interview Series conversation with IDG Chief Content Officer John Gallant, Cirne explained how New Relic gets IT and business execs on the same page in improving operations and customer experience, and he described the company's new tools for keeping highly virtualized private and public infrastructure in synch. He also talked about a 'unique' pricing scheme that recognizes the dynamic nature of computing today, and outlined why existing management tool vendors have a long way to go to catch up with New Relic. (Insider Story)

Company appears particularly interested in ability to analyse complex streaming data.

Dell wants to prove that you don't need a high-end GPU in your computer to create content for virtual reality headsets. Instead, the company wants to move VR content creation into the cloud with new computing products it plans to release. The goal is to add more mobility and security to VR content creation. Among the new products planned are thin clients that run applications stored in remote servers or appliances. The servers will have GPUs that power VR content creation on  virtual desktops. Virtual reality is an interesting market, and Dell will have products to talk about in the future, said Jeff McNaught, executive director of cloud client computing at Dell.

"Speak to Lana, she saw something like that last year," or "Ask Louis to do it, he's seen that a million times." We've all heard similar phrases within business — phrases that are uttered when something unusual happens, linking people together to help them get more experience in order to solve the challenge of those unusual circumstances. Imagine an 18-year-old being thrown directly into Major League Baseball, facing the best pitcher in the league: Everything that he is about to see is unusual, and the odds of failing are massive. The unusual is what trips us up and can cause us to fail. While some folks still talk about the three V's — velocity, variety and volume — with regard to big data, I think we are well beyond worrying about what makes data big. Instead the focus is "Why bother with big data?" For me, it comes down to a very simple statement:

This document provides recommendations and guidelines for enhancing trust in email, including transmission and content security recommendations.

Do big data algorithms treat people differently based on characteristics like race, religion, and gender? Mary Worth in her new book Weapons of Math Destruction and Frank Pasquale in The Black Box Society both look closely and critically at concerns over discrimination, the challenges of knowing if algorithms are treating people unfairly and the role of public policy in addressing these questions. Tech leaders must take seriously the debate over data usage — both because discrimination in any form has to be addressed, and because a failure to do so could lead to misguided measures such as mandated disclosure of algorithmic source code.

The long and winding road toward cellular carrier use of unlicensed spectrum took three steps this week.

Data integration may not sound as deliciously intriguing as AI or machine learning tidbits sprinkled on vanilla apps. Still, it is the bread and butter of many, the enabler of all things cool using data, and a premium use case for concepts underpinning AI.

The news puts a spotlight on the risks of free email services and, in turn, how it can put businesses at risk.

Today, I am proud to welcome a guest post by Claire Gilbert, Data Analyst at Gongos. For more on Gongos, see the description at the end of the post. It's fair to say that for those who run in business intelligence circles, many admire the work of Fast Forward Labs CEO and Founder Hilary Mason. Perhaps what resonates most with her fans is the moniker she places on data scientists as being 'awesome nerds'–those who embody the perfect skillsets of math and stats, coding, and communication. She asserts that these individuals have the technical expertise to not only conduct the really, really complex work–but also have the ability to explain the impact of that work to a non-technical audience. As insights and analytics organizations strive to assemble their own group of 'awesome nerds,' there are two ways to consider Hilary's depiction.

Citigroup is using software-defined storage to build an infrastructure that could last 25 years — while generations of hardware come and go. The financial services company needs to transform its storage architecture to deal with growing and changing demands, says Dan Maslowski, global head of storage and engineered systems. By simplifying its architecture, Citigroup expects to slash its operational expenses, which make up most of its storage costs. Citigroup's need for storage is growing so fast that if costs don't go down, the company's spending on storage might eat up its entire IT budget in a few years, Maslowski told an audience at the Storage Developer Conference in Santa Clara, California, on Tuesday.

With the ever-rising expectation of getting whatever we want, whenever we want it, companies are no longer waiting for orders to be placed. Instead, they are moving towards predictive fulfillment — using data and machine learning to foresee what their customers will buy and when, so they can send it to them pre-emptively.

by Brandon Rohrer, Principal Data Scientist, Microsoft R or Python? Torch or TensorFlow? (or MXNet or CNTK)? Spark or map-reduce? When we're getting started on a project, the mountain of tools to choose from can be overwhelming. Sometimes it makes me feel small and bewildered, like Alice in Wonderland. Luckily, the Cheshire Cat cut to the heart of the problem: "Would you tell me, please, which way I ought to go from here?" "That depends a good deal on where you want to get to," said the Cat. "I don't much care where–" said Alice. "Then it doesn't matter which way you go," said the Cat. "–so long as I get SOMEWHERE," Alice added as an explanation. "Oh, you're sure to do that," said the Cat, "if you only walk long enough." (Alice's Adventures in Wonderland, Chapter 6) The first step to choosing your tools is to choose a goal. Make it clear and keep it firmly in mind. That's most of the work. After that there are a few other things to consider and traps to watch out for, but you're 90% of the way there.




How does blockchain and cognitive computing affect fraud? Listen to the latest Finance in Focus podcast featuring Alex Tapscott, a blockchain expert and coauthor of a best selling book on the topic, who discusses how these technologies have the potential to eliminate fraud.

IBM Insight at World of Watson 2016 has oodles of opportunities for data engineers to enrich their skill sets with a bevy of best practices, peers to network with, pointers and tips to discover, sessions to attend and more. Consider five key reasons to get the green light from your organization to attend the conference, 24–27 October 2016, at Mandalay Bay in Las Vegas, Nevada.

IBM Insight at World of Watson 2016 has oodles of opportunities for data engineers to enrich their skill sets with a bevy of best practices, peers to network with, pointers and tips to discover, sessions to attend and more. Consider five key reasons to get the green light from your organization to attend the conference, 24–27 October 2016, at Mandalay Bay in Las Vegas, Nevada.

The hardest thing about adopting an enterprise collaboration platform can be adoption itself — getting employees to actually start up the new software and then turn to it whenever they need to communicate. Putting the software inside something that workers already use is one way to drive adoption and also make the communication tools more valuable. Cisco Systems knows this, and on Thursday the company announced a strategic alliance with Salesforce, its second big partnership in that direction after its headline-grabbing Apple iOS integration.

Spatial data and building information modeling (BIM) bring new tools for data visualuzation and analysis to building construction and operations. Information is now able to be shared across design teams, contractors and facility managers in real-time.

The regulation of chemicals is undergoing drastic changes with the use of computational models to predict environmental toxicity. This particular issue has not attracted much attention, despite its major impacts on the regulation of chemicals. This raises the problem of causality at the crossroads between data and regulatory sciences, particularly in the case models known as quantitative structure–activity relationship models. This paper shows that models establish correlations and not scientific facts, and it engages anew the way regulators deal with uncertainties. It does so by exploring the tension and problems raised by the possibility of causal explanation afforded by quantitative structure–activity relationship models. It argues that the specificity of predictive modelling promotes rethinking of the regulation of chemicals.

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science.

Running an eCommerce business is a challenging task. In addition to managing a huge scale of shipments and vendors, there are frequently multiple channels to manage as well. Those channels could include Amazon, eBay, Google Store, Rakuten, Alibaba, Etsy, as well as a self-managed website.

If there was any doubt that AI has officially arrived in the world of enterprise software, Salesforce just put it to rest. The CRM giant on Sunday announced Einstein, a set of artificial intelligence capabilities it says will help users of its platform serve their customers better. AI's potential to augment human capabilities has already been proven in multiple areas, but tapping it for a specific business purpose isn't always straightforward. "AI is out of reach for the vast majority of companies because it's really hard," John Ball, general manager for Salesforce Einstein, said in a press conference last week.

Data integration tools are evolving as enterprises ingest greater volumes of data and work with new data types. Here's a look at some of the top data integration tool providers in the market today.

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