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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO

Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need. Yet many are struggling to move into production because they don’t have the right foundational technologies to support AI and advanced analytics workloads. Some are relying on outmoded legacy hardware systems.

Analytics 205
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Organize and Process IoT Data Quickly Using AWS IoT Analytics

Cloud That

IoT device use has recently increased in applications such as agriculture, smartwatches, smart buildings, IoT retail shops, object tracking, and many more. Because IoT data is generally unorganized and difficult to evaluate, experts must first format it before beginning the analytics process. About CloudThat.

IoT 70
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Data confidence begins at the edge

CIO

Data-driven insights are only as good as your data Imagine that each source of data in your organization—from spreadsheets to internet of things (IoT) sensor feeds—is a delegate set to attend a conference that will decide the future of your organization. To learn more about the solution, read the white paper or watch the video.

Data 184
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Making Zero Trust Architecture Achievable

Tenable

As a leader in cybersecurity, Tenable was able to harness its expertise to best use security analytics, building out a program that had orchestration and enforcement capabilities through scanning and assessment, endpoint monitoring, traffic inspection and network discovery.

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Intel embraces SDN to modernize its chip factories

CIO

The collaboration with Cisco enables ACI to be deployed for factory floor process tools, embedded controllers, and new technologies such as IoT devices being introduced into the factory environment, according to Intel.

WAN 195
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From Reactive to Proactive: How Intelligent Maintenance & Operations is Transforming Manufacturing

Cherry Work

Going a step forward, it leverages IoT sensors, AI analytics, and cloud computing to anticipate machine breakdowns before they happen, optimizing finances and operations simultaneously. The downside? It led to over-maintenance. The advent of Industry 4.0 introduced a paradigm shift towards predictive maintenance. Cherrywork Industry 4.0

IoT 100
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Using Accelerators to Close the Real-Time Intelligence Gap

CTOvision

Today''s data-intensive analytic platforms offer a dizzying amount of data, originating from sensors, markets, social media, the Internet of Things, and countless other sources. You can download a white paper showing how this can be accomplished, complete with reference architecture, here. By Charles Hall.