Big Data News – 04 Jul 2016

Today's Infographic Link: Flight videos deconstructed

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Here are a few interesting studies breaking down salaries by job title, gender, skills, experience, location and other factors. Salary Survey: What pays most: R, Python, or SQL? Big Data and Data Science. Some reflections on compensation levels Chart: Salaries by Roles in Data Science O'Reilly 2015 Salary Survey for Data Scientists Click here to check out more salary surveys for data scientists and related jobs.

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Alation makes data more actionable via such innovative means as combining human experts and technology systems. The next BriefingsDirect Voice of the Customer big-data case study discussion focuses on the Tower of Babel problem for disparate data, and explores how Alation manages multiple data types by employing machine learning and crowdsourcing.

IBM Watson gets close with Cisco WebEx to improve collaboration. Hortonworks rolls out updates and initiatives at Hadoop Summit. MapR offers an update to please admins. MongoDB Atlas goes live with a managed cloud-based MongoDB service. It's all in our Big Data Roundup for the week ending July 3, 2016.

ClearDB, a pioneer in enterprise cloud database technologies, introduced its end-to-end Data Services Platform, a cornerstone that supports the company's vision to change the way databases are consumed.

Continuum Analytics, the creator and driving force behind Anaconda, a leading open data science platform powered by Python, announced that Recursion Pharmaceuticals, LLC, a drug discovery company focused on rare genetic diseases, is using Bokeh—-a Continuum Analytics open source visualization framework that operates on the Anaconda platform.

At the Cincinnati Insurance Companies, analytics is bridging the gulf between IT and business units and leading by example to form common measures and objectives.

The National Highway Traffic Safety Administration is looking into the circumstances surrounding a fatal accident involving a Tesla being driven under autopilot.

In this contributed article, Sham Mustafa, Co-founder & CEO of Correlation One, explores leveraging the benefits of machine learning for HR professionals during the hiring process for job applicants,

IBM (NYSE: IBM) and Cisco (NYSE: CSCO) announced they will partner to combine the market-leading strengths of each company to transform how knowledge-workers collaborate and work. The companies will form a suite of cloud-based workplace tools and applications infused with IBM Watson.

Today every part of the business is subject to new expectations, competitors, channels, threats and opportunities. Every business has the potential to be a digital business.   Businesses that…

GridGain Systems, provider of enterprise-grade In-Memory Data Fabric solutions based on Apache® Ignite™, announced the availability of GridGain Professional Edition 1.6, an in-memory computing platform enabling high-performance transactions that run 1,000x faster than disk-based approaches.

This paper proposes an algorithm called optimized relativity search to reduce the number of nodes in a graph when attempting to decrease the running time for personalized page rank (PPR) estimation. Even thoug…

The cloud promises new levels of agility and cost-savings for Big Data, data warehousing and analytics. But it's challenging to understand all the options — from IaaS and PaaS to newer services like HaaS (Hadoop as a Service) and BDaaS (Big Data as a Service).

Keeping pace with advancements in software delivery processes and tooling is taxing even for the most proficient organizations. Point tools, platforms, open source and the increasing adoption of private and public cloud services requires strong engineering rigor — all in the face of developer demands to use the tools of choice.

Big Data automation can mean writing dozens of scripts to process different input sources and aligning them in order to consolidate all this data and produce the required output. Why exactly do you need Big Data for your enterprise projects? Many industry observers have been noting that although a lot of enterprises like to claim that their big data projects are aimed at "deriving insights" that replace human intuition with data-driven alternatives, in reality though, the objective appears to be automation.

What does it look like when you have access to cloud infrastructure and platform under the same roof? Let's talk about the different layers of Technology as a Service: who cares, what runs where, and how does it all fit together. In his session at 18th Cloud Expo, Phil Jackson, Lead Technology Evangelist at SoftLayer, an IBM company, spoke about the picture being painted by IBM Cloud and how the tools being crafted can help fill the gaps in your IT infrastructure.

News this week included discussions on LTE-U, a massive health care data hack, telecom positions from Hillary Clinton, good new for small cells, IoT.

Tapjoy's data-driven business of serving 500 million global mobile users – or more than 1.5 million add engagements per day, a data volume of a 120 terabytes – runs with extreme efficiency. The next BriefingsDirect Voice of the Customer big data case study discussion examines how mobile app advertising platform Tapjoy handles fast and massive data – some two dozen terabytes per day – with just two part-time database administrators (DBAs).

Many organizations are considering use of a multi-cloud strategy, in which multiple cloud solutions are leveraged for a more complete cloud architecture.

Although EHR systems have advanced patient care, they have also made securing PHI far more complicated than the old lock-and-key approach.

Lots to see on the Big Data Blog in June! Please take a look at the summaries below for something that catches your interest. Use Sqoop to Transfer Data from Amazon EMR to Amazon RDS Customers commonly process and transform vast amounts of data with EMR and then transfer and store summaries or aggregates of that data in relational databases such as MySQL or Oracle.

The need to sufficiently distribute heat in hyperscale facilities has led to innovative approaches, many involving some form of liquid cooling.

After many years of research, misfires and frightening Hollywood plotlines, artificial intelligence (AI) is finally coming into its own and beginning to demonstrate significant business value. The combined forces of big data, human expertise and AI are being used across industries as diverse as healthcare and manufacturing, as well as within all aspects of business. IT operations is one area that AI is beginning to contribute to enormously. IT infrastructures are changing rapidly today, particularly hybrid cloud environments.

Finding insight in oceans of data is one of enterprises' most pressing challenges, and increasingly AI is being brought in to help. Now, a new tool for Apache Spark aims to put machine learning within closer reach. Announced on Friday, Sparkling Water 2.0 is a major new update from that's designed to make it easier for companies using Spark to bring machine-learning algorithms into their analyses. It's essentially an API (application programming interface) that lets Spark users tap H2O's open-source artificial-intelligence platform instead of — or alongside — the algorithms included in Spark's own MLlib machine-learning library.

Ideally, the ultimate output of big-data analysis can provide a company with a valuable competitive advantage. But those results aren't getting much additional security, according to an IDG Enterprise study of big-data initiatives.

Cisco defines the Internet of Everything (IoE) as bringing together people, process, data, and things to make networked connections more relevant and valuable than ever before-turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries. Cisco's message is obviously mainly economic and perhaps unintentionally, they forget to include other sociological, educational or philosophical aspects.

Ideally, the ultimate output of big-data analysis can provide a company with a valuable competitive advantage. But those results aren't getting much additional security, according to an IDG Enterprise study of big-data initiatives.

A guest blog post from Scott Schlesinger, Principal, America's EY Advisory EY and Hortonworks formed a strategic business alliance in August 2015 that is focused on helping our valued clients turn big data challenges into big business opportunities.  Recognizing that big data is transforming business and technology is driving that change, EY plays a significant role in… The post EY shares Key Observations from Hadoop Summit 2016 appeared first on Hortonworks.

We've shown a few times here how you can run R code on data in the cloud with Azure ML Studio, and even how to enable that code as a web service to be called from other applications. But what if you…

Instead of having fragmented copies of data everywhere, Cohesity uses APIs to access data that is indexed in an object-based storage system.

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