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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.

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Optimizing the Energy Sector with Data Analytics

Cloudera

With the right insights, energy production from renewable assets can be optimized and better predict the future of supply and demand. Organizations working in traditional energy generation will have to adjust costs by improving the efficiency of these plants. Investment is unavoidable, so the question becomes about smart investment.

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Streamlining supply chain management: Strategies for the future

IBM Big Data Hub

Effective SCM initiatives offer several benefits: Lower operational costs : By optimizing inventory levels , improving warehousing efficiency and streamlining order fulfillment processes, companies can save on storage, labor and transportation expenses.

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The extraordinary synergy of wi-fi and 5G in enterprise networks

CIO Business Intelligence

A severe thunderstorm is forecasted to roll through your suburb in the next hour. The benefits are extraordinary. As an IT leader, you deal with balancing benefits and budgets within the rapid pace of technological change every day. Automating routine tasks helps to improve efficiency and lower operating costs.

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Achieving Trusted AI in Manufacturing

Cloudera

As we navigate the fourth and fifth industrial revolution, AI technologies are catalyzing a paradigm shift in how products are designed, produced, and optimized. There are many functional areas within manufacturing where manufacturers will see AI’s massive benefits. That is a very low number.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

Like other CIOs, Katrina Redmond has been inundated with opportunities to deploy AI that promise to speed business and operations processes, and optimize workflows. The cost of implementing and running AI models can be quite high, so you have to be really careful in assessing the business worthiness of AI use cases,” he says. “The

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Asset lifecycle management strategy: What’s the best approach for your business?

IBM Big Data Hub

The following are the six stages of asset lifecycle management: Planning: In the first stage of the asset lifecycle, stakeholders assess the need for the asset, its projected value to the organization and its overall cost. Reduced maintenance costs and downtime: Monitor assets in real time, regardless of complexity.