Big Data News – 01 Nov 2016

Today's Infographic Link: 10 Ways to Make Work Easier

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Databricks, corporate provider of support and development for the Apache Spark in-memory big data project, has spiced up its cloud-based implementation of Apache Spark with two additions that top IT's current hot list. The new features — GPU acceleration and integration with numerous deep learning libraries — can in theory be implemented in any local Apache Spark installation. But Databricks says its versions are tuned to avoid the resource contentions that complicate the use of such features.

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Version 2.2 of Ansible will support Cisco (ASA); Dell; F5 Networks; Nokia SR-OS; Pluribus Networks (Open Netvisor) and VyOS devices.

O'Reilly Media's 4th annual survey of data professionals looks at tools, languages, gender, geographies, and a host of other factors that are predictors in terms of how much data workers can expect to earn. Where do you fit?

Investments in predictive analytics, dashboards, and KPIs are coming to CRM lead management offerings, according to Gartner's most recent Magic Quadrant report for the category. The finding is reflective of an increasing number of IT organizations aiming to deliver more and better intelligence for sales and marketing users.

Why do many organizations that invest heavily in analytics and hire data scientists to slice and dice the data end up frustrated? Here's how to make predictive analytics powerful. Keep on reading: Predictive analytics: the knowledge worker is the battleground

Establishing a digital governance plan can be a challenge, but with the right education and tools, the job can be made a lot simpler.

R 3.3.2, the latest update to the R language, was released today. Binary releases for Linux and Mac are available now from your local CRAN mirror, and the Windows builds will be available shortly. As a minor update to the R 3.3 series, this update focuses mainly on fixing bugs and doesn't make any major changes to the langauge. As a result, you can expect existing scripts and packages to continue to work if you're upgrading from R 3.3.1. This update includes some performance improvements (particularly in calculation of eigenvalues), better handling of date axes in graphics, and improved documentation for the methods package.

Organizations need to develop skills and technology to manage Big Data operations across multiple data centers, likely across large geographic areas.

Banks generate all kinds of reports, but not all of them can explain customer behavior or predict a customer's next move. Find out how IBM Customer Insight for Banking uses cognitive analytics to give you vital insight into customer behavior, allowing you to predict financial events, prevent churn and proactively engage your customers as individuals.

Customers' desires have changed dramatically through the years. Most notably, modern consumers expect organizations to know them–and, what's more, to anticipate their needs. In such an environment, traditional approaches to customer segmentation are giving way to new methods of engaging with customers. IBM's Client Insight solutions are tapping into the power of transforming customer segmentation through cognitive insight. As they do, they are helping organizations in several ways: Generating dynamic segments based on client behavior Applying industry-specific models to deliver actionable insights Predicting future lives and financial events of clients Using insights to drive personalized client offers In this video, recorded live on location at the Financial Services Sector (FSS) Forum, Marc Andrews, vice president of IBM Watson Financial Services, and guest speaker Jim Marous, owner of the Digital Banking Report and copublisher of the Financial Brand, trace the trends pointing toward the need for enhanced customer insight solutions for financial services: Not only is data collected on every aspect of life, but this data is also powerful enough to connect–and even interact–with customers. The trend toward financial inclusiveness is connecting financial institutions with previously disregarded or overlooked populations. The modern consumer can use a smartphone to make a down payment on a fully electric car that can park itself in a driveway.

Project CloudWAN uses network virtualization, microservices and controller technology hosted in the cloud to manage physical and virtual appliances.

We aren't doing enough to eradicate zombie apps from attacking in the first place.

A new Gartner Maverick report says that annual physical medical exams and primary care doctors are about to be disrupted by IoT medical devices and algorithm. Here's how IT must shift to accommodate the change.

Predicting the future is not a theoretical superpower. It is a skill we already rely on to make decisions, and like any other skill it can be rapidly improved with deliberate practice. Unsurprisingly, deliberate practice looks like making predictions within a domain and comparing the results to reality. This year I've built a culture of doing just that at Twitch. It's the most exciting work I've ever done.

Successful marketing automation strategies are highly dependent on big data. Brands should understand the role big data plays and have a clear strategy to collect and use it effectively.Why Marketing Automation Depends on Big DataBig data plays a key role in marketing automation. Here are some reasons big data is so important:

For many organizations, existing data-analytics infrastructures are too complicated, and it's difficult to find qualified job candidates to helm analytics projects.

Spreadsheets are excellent tools as far as they go–but how far can they truly go? If you're pushing your spreadsheet-based solutions beyond their viable limits, then they might be doing more harm than good. Discover what considerations you shouldn't ignore when using spreadsheets for statistical analysis, and explore alternatives that are designed to help you expand your limits without putting your organization at risk.

Microsoft is much more tightly connecting the hardware and software.

Sanovi Technologies is a provider of orchestration and visualization tools optimized for managing data protection.

New funds aimed to fuel growth by accelerating development, expanding sales and marketing, and growing international operations.

In recent years, the best-performing systems in artificial-intelligence research have come courtesy of neural networks, which look for patterns in training data that yield useful predictions or classifications. A neural net might, for instance, be trained to recognize certain objects in digital images or to infer the topics of texts. But neural nets are black boxes. After training, a network may be very good at classifying data, but even its creators will have no idea why. With visual data, it's sometimes possible to automate experiments that determine which visual features a neural net is responding to.

It seems that Google Fiber — which is a division of Alphabet — has come to a crossroads.

At the first OpenPower European Summit, the group unveiled new projects and offerings based on the open architecture.

The recent DDoS attacks launched from IoT devices demonstrate that the internet of things spans all parts of IT and that most companies deploying it still need a lot of help. That's the message from ARM, the chip design company behind nearly every smartphone and a big chunk of IoT, at its annual TechCon event this week in Silicon Valley. Small, low-power devices like sensors and security cameras are the most visible part of IoT, and they're right in ARM's wheelhouse as the dominant force in low-power chips. But on Wednesday, the company highlighted a cloud-based SaaS product rather than chips or edge devices themselves. IoT depends on back-end capabilities as much as edge devices, and the company wants to play a role in all of it.

End users think they are tech savvy or knowledgeable about security issues, but in reality, they aren't as informed as they think.

SAP aims to close the divide that exists between most operational systems and backend IT platforms that need to converge in an IoT environment.

We recently hosted a webinar on the newest features of Hortonworks DataFlow 2.0 highlighting: the new user interface new processors in Apache NiFi Apache NiFi multi-tenancy Apache NiFi zero master clustering architecture Apache MiNiFi One of the first things you may have noticed in Hortonworks DataFlow 2.0 is the new user interface based on Apache…

Over the last few months, Microsoft has turned around its SharePoint platform and embarked on a mission to modernize the popular collaboration and portal product. This is great news for customers, who can look forward to a number of improvements, including a complete overhaul of SharePoint's aging web user interface. However all the change introduces a lot of uncertainty. While it's clear that Microsoft is investing in SharePoint again, how can enterprise customers invest without worrying that Microsoft will make their work obsolete? The SharePoint experts at BlueMetal have written a white paper to address these concerns, and to help clients plan a roadmap to the Future of SharePoint.

IT organizations should prioritize their self-service analytics tools projects to enable business users to experience the value of analytics and big data investments.

As much as we data scientists would like to work solely in R, there inevitably comes the time when our managers or customers want to see the fruits of our labours as a Word document or PowerPoint presentation. And not just any old document: it needs to be in the official corporate template, and will no doubt go through a series of back-and-forth revisions — marked up directly in the document — before it's considered final. R has several options for generating Word and PowerPoint documents, notably RMarkdown and Slidify. But in both these cases, R is in the driver's seat, and if you want to make any changes to the document that will persist through changes to the R code, you'll need to make those changes with R.

Apache Spark has been Open Source's new kid on the block. Companies are using Spark to develop sophisticated models that would enable them to discover new opportunities or avoid risk. But what does the future or at least the near future hold for Spark? In this blog we have outlined five trends we see in…

Announcements related to IBM Watson and cognitive continue to pour forth from IBM Insight at World of Watson 2016. Discover what the conference has highlighted thus far in this comprehensive overview.

The complexity of multiple data sources contributing to the rising tide of data has executives at many enterprises up at night because of concerns involving risks, regulations and compliance. See why information governance is especially vital in today's complex ecosystem of voluminous data sources to help ensure protection of the information in collaborative, integrated environments.

Over the past two years IBM has been moving in the direction of being a data driven cognitive and cloud company. As part of this transformation, IBM has acquired The Weather Company that provides some of the most accurate weather data to pinpoint the impact of impending weather event to a specific address.

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