Big Data News – 21 Oct 2016

Today's Infographic Link: X-ray F1

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Last year, MIT researchers presented a system that automated a crucial step in big-data analysis: the selection of a "feature set," or aspects of the data that are useful for making predictions. The researchers entered the system in several data science contests, where it outperformed most of the human competitors and took only hours instead of months to perform its analyses. This week, in a pair of papers at the IEEE International Conference on Data Science and Advanced Analytics, the team described an approach to automating most of the rest of the process of big-data analysis — the preparation of the data for analysis and even the specification of problems that the analysis might be able to solve. The researchers believe that, again, their systems could perform in days tasks that used to take data scientists months."

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NEWS ANALYSIS: EMC'S data center technology held center stage at the first combined Dell EMC World conference, but Michael Dell says that appearances aside, "this is one company."

Once upon a time, there was the original R Graph Gallery. Sadly, it's been unavailable for several years. Now there's a new R Graph Gallery to fill the void, created by Yan Holtz. It contains more than 200 data visualizations categorized by type, along with the R code that created them. You can browse the gallery by types of chart (boxplots, maps, histograms, interactive charts, 3-D charts, etc), or search the chart descriptions. Once you've found a chart you like, you can admire it in the gallery (and interact with it, if possible), and also find the R code which you can adapt for your own use. Some entries even include mini-tutorials describing how the chart was made. You can even submit your own graph, if you'd like to have it displayed in the gallery as well. It also includes a number of graphics that are not data visualizations, but rather Data Art: artistic creations based on data and/or code, including this neat rendering of BB-8 in R code. Sadly it doesn't include any examples from the Accidental aRt collection, nor this new Dadaism from Stephen Turner. What the 2016 electoral map would look like if I made it in #Rstats on the first try.  

Google introduces its Coldline option for archiving rarely used data, as well as price cuts and refreshes across all storage services.

AI was mostly discussed by futurists and screenwriters just a few years ago. Now, it is at the center of many corporate and business functions.

Snowflake, the cloud-based data warehouse solution co-founded by Microsoft alumnus Bob Muglia, is lowering storage prices and adding a self-service option, meaning prospective customers can open an account with nothing more than a credit card. These changes also raise an intriguing question: How long can a service like Snowflake expect to reside on Amazon, which itself offers services that are more or less in direct competition — and where the raw cost of storage undercuts Snowflake's own pricing for same? [ InfoWorld's quick guide: Digital Transformation and the Agile Enterprise. | Download InfoWorld's essential guide to microservices and learn how to create modern web and mobile applications that scale. ] Open to the public The self-service option, called Snowflake On Demand, is a change from Snowflake's original sales model. Rather than calling a sales representative to set up an account, Snowflake users can now provision services themselves with no more effort than would be needed to spin up an AWS EC2 instance.

It's easy to forget about the ghosts of servers past, continuing to consume electricity and exposing organizations to potentially malicious attacks.

The Internet of Things (IoT) is under attack, and really, it was only a matter of time.

It's India meets Indianapolis: Bangalore-based consulting firm Wipro is buying Appirio for $500 million to bulk up its cloud applications business. With more resources behind it, cloud services vendor Appirio will be in a better position to fight back against big consulting firms like Accenture and Deloitte, which "have garnered disproportionate market share" in the cloud services market in recent years, Appirio CEO Chris Barbin wrote in a blog post explaining the deal. Appirio, based in Indianapolis, offers a range of cloud applications integration services, many of them built around — a logical fit since it grew out of Salesforce's AppExchange startup incubator. The 10-year-old company also partners with Workday, Google and Amazon Web Services, and numbers Facebook, eBay and Coca-Cola among its customers.

Dell is quietly working on integrating virtual reality with the Microsoft Skype for Business video conferencing cloud service.

Analytics is all the hype these days, and for good reason. Taking the power of analytics and applying it to the backup and recovery process will be a boon for the IT industry. Analytics will help deal with the data hoarding epidemic and ensure critical data is backed up, without financing storage space and data management for all those pictures of your aunt's cats.

Guest Author: Patti Mizulo, Senior Director, Big Data Partner Program, Dell EMC So close and yet so far. That is often what it's like when you're trying to wrangle big data trapped in siloes and extract valuable business insights. It can take weeks or months using traditional methods. Chances are, your data sits on multiple systems across your company or even outside your data center. It's probably in a variety of formats, both structured and unstructured. No wonder data analysts typically spend up to 80 percent of their time amassing and preparing data before they can focus on analytics. [1] Dell EMC™ has solved this vexing problem with the new Analytic Insights Module.  This self-service, cloud-native data analytics solution is an effective way to transform big data into actionable insights.   

Instances of OpenStack managed by Mirantis will be hosted on IT infrastructure provided by NTT as a service.

Though online interest in the presidential election has never been higher, social media sentiment about the candidates is in the basement.

The total number of ransomware attacks rose by 13 percent in September alone, say Check Point cybersecurity researchers.

Snowflake, a cloud data warehouse pure play, has decided to slash prices on storage, and make its money on compute resources and management. Will this force Amazon, Microsoft and Google to respond in kind?

From the impact of wearable technology to the potential for boosting cancer research, there's been a lot of buzz about big data in the healthcare space. However, the true vision of big data in healthcare lies not in individual data collection or disparate applications, but in the potential of combining healthcare data to create new resources for doctors.

When it comes to disaster preparedness, predicting disasters is one of the biggest problems governments have. That is where big data technology and predictive analytics step in and provide the solution. Over recent years, big data has been able to help scientists and disaster aid agencies narrow down to the hardest hit areas.

The driving force behind enterprise data analytics today is obtaining valuable insights more quickly from large, diverse data sets. A key issue blocking easier access for data scientists, business analysts and IT has been finding an alternative to the current data modeling process.

Those who attended the SHRM annual conference heard over and over again the three holy words of modern HR: culture, strategy, and analytics.

Introduction:Few IT or business professionals would argue over the value of a well-constructed disaster recovery plan, with so many businesses and organizations depend on data systems for their most basic business functions. Savvy business owners know that it is no longer only a matter of protecting your data, but also of saving your business.

I recently had someone ask me, "For years we've talked about changing analytics from 80% data prep and 20% analytics to 20% data prep and 80% analytics, yet we still seem stuck with 80% data prep. Why is that?" It is a very good question about a very real issue that causes many people frustration.I believe that there is actually a good answer to it and that the perceived lack of progress is not as bad as it first appears. To explain, we need to differentiate between a new data source and/or a new business problem and existing ones we have addressed before.

It wasn't too long ago that big data was thought of as a niche concept, something reserved for only those companies that were especially tech-savvy. Fast forward a few years and the popularity of big data has increased tremendously, with businesses of all shapes and sizes using it. Such is the way with most technologies, and Apache Spark is no exception. This should certainly come as no surprise considering how comfortable organizations have become with big data analytics, but this impressive growth deserves mentioning.

As data and analytics become a more integral part of business processes in an organization, so the non-DBAs among us might start to feel lost in a sea of technical terms which are frequently thrown around by technical teams.

The term "people analytics" is being used more frequently in HR and management circles, and with good reason. People analytics as a discipline, and a corporate function, is taking off.

AT&T announced it will partner with Amazon Web Services (AWS) to let joint customers use AWS cloud services with the AT&T network.

Not all IT services are created equal, and that's typically (but not always) directly correlational with how much you're paying. It may sound a little cliche, but truly you get what you pay for when it comes to technology services for your business. When things are working fine, it's hard to make the decision to move forward with any technology innovation or changing companies.

Analysts predict that by 2020, Robotic Process Automation solutions will see a compounded annual growth rate of 60.5 percent. Employers are increasingly looking to robotic software to automate many of the data tasks currently completed by humans, for clear reasons, but the process isn't as cut-and-dry as it first appears.To understand the true ramifications of RPA when it comes to data tasks, we have to look a little closer at what the technology means — and where it still needs improvement.

Predictive analytics / machine learning / artificial intelligence is a hot topic — what it's about?

After Matt Francis' "50 Shades of Data" at #Data15 I really got to thinking about color, it's usage and the planning of pallets. So I thought that I would share some of the tools that I use for testing, planning and plotting color for use in Tableau.

There are endless numbers of advertising mediums to grow your brand over the Internet. Many companies rely on Google Adwords and Facebook advertising, but there are other strategies worth exploring. Media buying is one of them.Media buying is the purchasing of advertisements from media companies. Over the Internet, it more specifically refers to the purchasing ads based on individual websites. Media buying typically relies on banner adverting.

The ongoing debate surrounding ad blocking might never die. Its impact can be felt by the billions of internet users, all of which have been hit by unwanted ads at least once. But at the same time, millions of other companies have their ads unseen. As end users, we may think of ad blockers as sources of power, a tool to use in order to gain some control in our browsing experience. However, we also favor net neutrality because we want everyone, including ourselves, to be visible.

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