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Enterprises rely on 3 types of IoT analytics from their selected IoT platforms. By testing multiple IoT platforms, an enterprise can identify best-in-class analytics capabilities.
Data scientists are the MVPs of any IoT program, but difficulties preparing and leveraging data threaten how quickly they can deliver. Knowing what’s lurking in the shadows can streamline the most difficult processes.
In data-intensive WiFi environments, artificial intelligence and machine learning are emerging as essential tools for ensuring stable, secure connectivity.
Data centers are an integral component of private and hybrid cloud strategies. Better automation can provide greater visibility and simplified operations.
As the volume of data that organizations collect continues to grow, storing everything simply isn’t cost effective. A strategy that balances data reduction with fidelity is increasingly vital.
Network World 8th annual State of the Network survey looks at high-priority SDN, IBN, SD-WAN, network-security trends.
Many organizations are collecting and hoarding all sorts of data but completely failing to extract any real value from it. Successful businesses are employing data analysis for a tangible competitive edge.
The Internet of Things promises to make healthcare cheaper and better in a wide variety of ways, but many of the benefits are still stuck in the waiting room.
Data scientists are a key component of an IoT deployment, however in-house data science resources can become thinly stretched. Outsourcing data scientists has the dual benefit of helping keep IoT initiatives moving forward while freeing up internal r
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