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How AI and IoT Solutions Can Improve Your Business

Smart Data Collective

In today’s modern era, AI and IoT are technologies poised to impact every part of the industry and society radically. In addition, as companies attempt to draw better significance from the huge datasets gathered by linked devices, the potential of AI is accelerating the wider implementation of IoT. l Improved Risk Management.

IoT 132
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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Collecting workforce data as a tool for talent management. Collecting workforce data as a tool for talent management. Data enables Innovation & Agility.

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How adopting sustainability as a service can drive business success and help the planet

CIO Business Intelligence

This is designed to help manufacturing, transportation and other industries accelerate sustainability initiatives and make data-driven decisions to reduce their carbon footprint and become more efficient through the intelligent use of IoT connectivity. Data lives in silos across the IT and OT environment.

IoT 101
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Cropin’s agriculture industry cloud to provide apps, data frameworks

CIO Business Intelligence

Dubbed Cropin Cloud, the suite comes with the ability to ingest and process data, run machine learning models for quick analysis and decision making, and several applications specific to the industry’s needs. The suite, according to the company, consists of three layers: Cropin Apps, the Cropin Data Hub and Cropin Intelligence.

B2B 105
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Sharing Responsibility for Data Security in the Cloud

CIO Business Intelligence

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. Here again, the customer is responsible for securing the guest OS, applications, and data.

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Understanding the security shared responsibility model in an as-a-service world

CIO Business Intelligence

As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and risk management, with clear boundaries of shared responsibility. Here again, the customer is responsible for securing the guest OS, applications, and data.

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Streamlining supply chain management: Strategies for the future

IBM Big Data Hub

Big data and predictive analytics are increasingly being used to improve forecasting accuracy, allowing businesses to respond more effectively to changes in customer needs. Real-time tracking systems, often enabled by Internet of Things (IoT) devices, help companies monitor their supply chain accurately and immediately.