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Data Management // Hardware/Architectures

Who Should Own RPA?

Enterprises are running into challenges with robotic process automation because lines of business or IT are missing the bigger picture. Thinking strategically and cross-functionally helps.

By Lisa Morgan Freelance Writer, 2/18/2020

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Engineering Tiny Machine Learning for the Edge

As developers face the challenge of making complex AI and machine learning applications work on edge-computing devices, options to support Tiny ML are emerging.

By James Kobielus Research Director, Futurum, 2/6/2020

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IT Careers: 10 Job Skills in High Demand This Year

If you're looking to add skills to your resume, experience with these technologies might help you land a new job or promotion.

By Cynthia Harvey Freelance Journalist, InformationWeek, 2/3/2020

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Data Management Meets Multi-Cloud Environments

Many big enterprises are committed to public cloud, but they may just be getting started with data management efforts in multi-cloud environments.

By Jessica Davis Senior Editor, Enterprise Apps, 1/30/2020

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Next Evolution of Data Capture Tech Transforms Retail

Eye-tracking, facial recognition, sensors, and digital displays gather data that retailers can use to fine-tune their strategies.

By Joao-Pierre S. Ruth Senior Writer, 1/23/2020

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GIS Drives Superhighway to Analytics Future

The Pennsylvania Turnpike may be 80 years old, but its GeoAnalytics program is leveraging geographic information to drive the future.

By Jessica Davis Senior Editor, Enterprise Apps, 1/21/2020

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SIM Study Points to Lax Focus on Cybersecurity

Despite ranking at the top of respondents� concerns, organizations still show gaps in acting on cybersecurity.

By Joao-Pierre S. Ruth Senior Writer, 1/8/2020

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AI Explosion Brewing in the Cloud for 2020

Expert from Accenture sees the cloud as the gateway for enterprises to access more innovation this year.

By Joao-Pierre S. Ruth Senior Writer, 1/3/2020

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Rick Perry and Breaking Down Hope vs. Hype at The AI Summit

Learn some of the aspirations government has for AI and ways to see through the froth.

By Joao-Pierre S. Ruth Senior Writer, 12/13/2019

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GPUs Continue to Dominate the AI Accelerator Market for Now

As enterprises embark on AI and machine learning strategies, chip makers like NVIDIA, Intel and AMD are battling to become the standard hardware providers.

By James Kobielus Research Director, Futurum, 11/27/2019

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Watch Out: 7 Digital Disruptions for IT Leaders

Here are seven digital disruptions that you may not see coming.

By Jessica Davis Senior Editor, Enterprise Apps, 11/18/2019

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10 Data and Analytics Trends for 2020

Data and analytics are permeating all parts of the digital enterprise. Here are the trends you need to watch in the years ahead.

By Jessica Davis Senior Editor, Enterprise Apps, 11/12/2019

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How IT Supports the Data Science Operation

Data science and IT no longer are separate disciplines. Think of it as a partnership.

By Mary E. Shacklett Mary E. Shacklett, 11/4/2019

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Six Inevitable Technologies and the Milestones They Unlock

Grand-scale technologies act as nodes of progress that spark continued innovation. Here are several that will continue to impact society.

By Beth Devin, Managing Director, Citi Ventures , 10/3/2019

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IT Careers: 12 Job Skills in Demand for 2020

Employers will likely be looking to fill these kinds of IT positions in the coming year, building out their teams' tech skills.

By Cynthia Harvey Freelance Journalist, InformationWeek, 10/1/2019

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Talent Alert: Data Science Help is Coming

But will the flood of candidates solve your data problems? Here are a few issues to mull and tips on how to attract/retain data scientists in this hot market.

By Dirk Beyer, SVP Data Science Research, Neustar , 9/27/2019

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How to Choose the Right Analytics Skills

Just because an analyst hits the ground running does not mean that analyst has the ongoing breadth needed to solve every day analytics problems.

By Pierre DeBois Founder, Zimana, 9/10/2019

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Lineage Metadata: The Fuel for Data Governance

The best way to achieve data quality is by combining or blending these three techniques: decoded lineage, data similarity lineage and manual lineage mapping.

By Moshe Kranc, CTO, Ness Digital Engineering , 8/1/2019

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IBM�s Rob High and Rumjog�s Thomas Young Talk Edge Computing

The scope of what can be done through edge computing is growing fast, but it will take more talent and new strategies to reap the benefits.

By Joao-Pierre S. Ruth Senior Writer, 7/26/2019

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Slash Data Center Costs by Optimizing Hardware Investments

CIOs can quickly find themselves on an expensive hardware-replacement treadmill, but it doesn�t have to be that way.

By Gordon Smith, CEO, Sagent , 7/25/2019

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