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The latest big data news and articles

The Myth of Entry-level Data Science

In this special guest feature, Kevin Safford, Sr. Director of Engineering for Umbel offers a no-nonsense look at how to answer the proverbial question “How can I become a data scientist.” To understand how to become a data scientist, it’s best to get on the same page on what data science is. And if this is your career path, get accustomed to always defining your domain before you begin.

Book Review: Weapons of Math Destruction by Cathy O’Neil

Normally the books I review for insideBIGDATA play the role of cheerleader for our focus on technologies like big data, data science, machine learning, AI and deep learning. They typically promote the notion that utilizing enterprise data assets to their fullest extent will lead to the improvement of people’s lives. But after reading “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy,” by Cathy O’Neil, I can see that there’s another important perspective that should be considered.

Zebra Medical Vision to Make AI in Healthcare Accessible & Affordable for All

Zebra Medical Vision, the leading deep learning imaging analytics company, is announcing AI1: a new suite that offers all its current and future algorithms to healthcare providers globally for $1 USD per scan. This is another step in the company’s quest to provide high quality, affordable care to the world’s population.

Virtual GPUs: Accelerate Mobility, Productivity & Security in Healthcare

Many hospitals have turned to virtualization to provision high performance, secure virtual workstations using the compute power of a single physical hardware resource. That’s according to a new report from HPE, that explores how virtual GPU technology is helping to modernize healthcare data workloads.

Information Builders Improves Ease of Use and Analytics Workflow With Latest Version of WebFOCUS

Information Builders, a leader in business intelligence (BI) and analytics, information integrity, and integration solutions, announced the launch of WebFOCUS 8.202, the latest version of its award-winning BI and analytics platform. Drawing on extensive behavioral and user experience design research, the new release provides an enhanced user interface and key workflow improvements that reduce the amount of time and skill needed to derive data-backed insights.

How Data is Stored and What We Do With It

The amount of data in the world is increasing as our storage devices are becoming smaller and more powerful. With this abundance of data there is an increased focus on the ways we retrieve, manipulate, and use the data we’ve stored. To learn more, checkout the infographic below created by our friends over at Rutgers University’s Online Master of Information.

GPU-Accelerated Database & Analytics Platform Introduces SpotLyt, a Visual Analytics Tool for Billion Row Data Sets

Brytlyt, a leading GPU-accelerated database & analytics platform, is now offering a real-time visualization analytical tool, SpotLyt, designed for massive data sets. It allows data scientists and analysts to interactively analyze billion row data sets in real-time, helping them discover correlations and anomalies in ways previously thought impossible.

Large Scale Deep Learning with TensorFlow

In this video presentation from the Spark Summit 2016 conference in San Francisco, Google’s Jeff Dean examines large scale deep learning with the TensorFlow framework. Jeff joined Google in 1999 and is currently a Google Senior Fellow.

Slemma Embeds Datawatch Monarch Swarm Into Data Visualization Offering for Improved Data Quality, Collaboration and Governance

Datawatch Corporation (NASDAQ-CM: DWCH) announced that Slemma, a data analytics tool for small and medium-sized businesses, is integrating Datawatch Monarch Swarm into its data visualization offering to enhance data access, data quality, information sharing and team collaboration, while enforcing IT governance.

The Practical Guide to Managing Data Science at Scale

Our friends over at Domino Data Lab, Inc. have written a new whitepaper “The Practical Guide to Managing Data Science at Scale” that aims to demystify and elevate the current state of data science management. They identify consistent struggles around stakeholder alignment, the pace of model delivery, and the measurement of impact. The root cause of these challenges can be traced to a set of particular cultural issues, gaps in process and organizational structure, and inadequate technology.