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Data Management // Hardware/Architectures

10 Things You Should Know About Deep Learning

This type of machine learning is going to become increasingly important in analytics and enterprise applications.

By Cynthia Harvey Contributor, NetworkComputing, 4/23/2018

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Ethical Tech: Myth or Reality?

Technology innovation is accelerating and so are the impacts of technology on society. As machine intelligence gets baked into more products and services, as more human tasks become automated, and as more industries are disrupted, the tech industry needs to think differently. Here's why.

By Lisa Morgan Freelance Writer, 4/4/2018

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Five Traits to Look for in a Data Protection Officer

It's crucial for a data protection officer -- required under the EU's GDPR -- to have a enterprisewide view of an organization's stored data and how it is used, or not used.

By Kon Leong, president, CEO and co-founder, ZL Technologies , 4/3/2018

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Neuroevolution Will Push AI Development to the Next Level

Next up for developing artificial intelligence systems is automated neural-net architecture search.

By James Kobielus Lead Analyst, SiliconANGLE Wikibon, 3/30/2018

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Real-Time Analytics is Spreading and Getting Easier

Is your organization in production with real-time analytics and event stream processing? Are you doing a pilot of the technology? Here's a look at where the technology is today, along with some of the more popular use cases.

By Jessica Davis Senior Editor, Enterprise Apps, 3/22/2018

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3 Myths About the Site Reliability Engineer, Debunked

Emily Johnson, Digital Content Editor, InformationWeek

As automation becomes a fact of life, newer roles, such as site reliability engineer, emerge. For IT pros looking for their next move, here’s a little background about the role as well as some common misunderstandings about it.

By Emily Johnson Digital Content Editor, InformationWeek, 3/20/2018

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Beware the Dangers of 'Drive Thru' Analytics

John Edwards, Technology Journalist & Author

Cutting corners isn't the path to analytics success. Data science requires an enterprise commitment.

By John Edwards Technology Journalist & Author, 3/15/2018

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Reshaping Skillsets in the Age of Analytics

Automation and greater involvement by business managers with the analytics team are just a couple of the changes that are in store for data science.

By Rich Wagner President and CEO of Prevedere, 3/15/2018

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The Evolution Away from Conversational User Interfaces

Those digital devices that get you through the day will get less chatty and more focused on working for you.

By James Kobielus Lead Analyst, SiliconANGLE Wikibon, 3/13/2018

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The New Data Playbook: Automation, Mass Data Literacy

How will enterprise organizations scale Agile data and analytics programs in the future? Gartner says trust, diversity, and data literacy all will contribute to mastering tomorrow's complexity.

By Jessica Davis Senior Editor, Enterprise Apps, 3/8/2018

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Conversational AI is Ready for Prime Time

Don't lump the various types of AI-based technologies into one basket. There are differences among them, as a look at call center tech highlights.

By Stanton Jones, director & principal analyst, Information Services Group , 3/6/2018

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Outbrain Outgrows Initial Big Data Infrastructure, Migrates

Content discovery platform Outbrain launched its first Hadoop pilot about 5 years ago, on the free version of the technology, giving it the flexibility to experiment. But the company recently made some changes to update its big data program.

By Jessica Davis Senior Editor, Enterprise Apps, 3/1/2018

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Don’t Lift and Shift Big Data Analytics, Lift and Optimize

Advancing through the digital era with a greater use of self-service analytics doesn't mean that you have to trash proven analytics tools and techniques.

By Jen Underwood Impact Analytix, 2/26/2018

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Rethinking IT: Why Computer Scientists Should Care about Art, Chemistry and Biology

Career advice for computer scientists and IT professionals: Talk to, listen to, and work with your peers in a multi-disciplinary environment.

By Jeff Welser, VP and Lab Director, IBM Research - Almaden , 2/23/2018

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How to Begin Integrating AI into Data Center Operations

Data center automation is inevitable. Here's how to do it right from the beginning.

By John Edwards Technology Journalist & Author, 2/21/2018

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Avoid These Pitfalls to Get Maximum Value from Data Science

Data science techniques are getting better, cheaper, and easier to use. Even small and medium sized organizations can now tap these technologies. But, if you fail to properly introduce, support, and integrate data science capabilities, a lot of money can be wasted.

By H.P. Bunaes, Chief Data Officer , 2/21/2018

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Ebates Migrates the Data Analytics Stack: SQL Server to Hadoop

Ebates, the business that provides discounts and incentives to customers of online retailers, needed to move from its SQL server to a system with more processing capacity. The Hadoop cluster it chose fit the bill and provided some unexpected benefits.

By Jessica Davis Senior Editor, Enterprise Apps, 2/14/2018

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Taking the Brakes off the Internet of Things

If you get the sense that Internet of Things adoption is sluggish, consider that it is going through a normal process.

By Tim Sherwood, VP, Business Development, Mobility & IoT Solutions, Tata Communications , 2/14/2018

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How AR/VR Analytics May Help Your Business

Alternative and virtual realities provide organizations with new opportunities to reimagine product demos, employee training and more. As the systems collect and generate data, there are opportunities to use the new streams in innovative ways.

By Lisa Morgan Freelance Writer, 2/13/2018

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The Future of Information Technology is Intelligence

Traditional IT has to make way for the intelligence-based business model.

By Ben Lamm, Co-founder and CEO of Conversable , 2/12/2018

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