Joe McKendrick

The convergence of computing environments, from edge to the central server, is forming the foundation of the emerging real-time enterprise.

Engineers, developers, entrepreneurs, government authorities, and others will find it fruitful to combine these technologies in large-scale efforts.

AI swarm systems draw input from individual people or machine sensors and then use algorithms to optimize the overall performance of the group in real time.

AIOPs represents a mind shift from humans watching systems and reacting to one where the systems automatically alert the human to an issue and take corrective actions on their own.

Data science skills are scarce. Companies cannot afford to find and hire developers with the qualified background to create and maintain custom analytics solutions.

Potential obstacles to implementing streaming analytics include outdated architectures, limited staff availability, and a lack of skills.

A majority of companies (85%) agree that automation needs to play a greater role in supporting their business continuity strategies.

Real-time data without context can be either too troubling or not troubling enough, leading to panic and wrong decisions.

Applications will enable secure data transfer for sensors across the supply chain to establish the provenance and authenticity of goods.

Securing IoT devices and staying ahead of certificate expiration have become top strategic priorities for IT teams

The growing power of computers combined with advances in AI make the fast-learning virtual worker a reality.

The study found that when it comes to smart factories, the auto industry is more bullish than its peers in manufacturing.