Joel Hans

Stream processing acts on the constant flow of real-time data allowing businesses to shift their operations toward real-time responsiveness.

Stream processing and real-time responsiveness can significantly improve existing customer care processes and data flows.

Retailers are looking to stream processing to personalize offerings in real time, activate dynamic pricing, and more.

Stream processing is transforming how the most ambitious financial services companies serve customers and how they operate in complex, always-changing environments.

By processing and deriving insights at the speed of real-time data, a stream processing platform becomes the core of all new competitive advantages, use cases, and innovations.

Enabling real-time data democratization is no easy task philosophically, organizationally, or technologically.

In many jurisdictions, organizations are now required to store user data in the country where it’s collected and users live, which creates an enormous technical problem. A sovereign cloud might be the solution.

Despite the growth and variety in edge computing device availability, the path toward thin or thick edge isn’t exactly clear.

The report also claims there’s a potential to squeeze out an additional $2.6 trillion in revenue if more companies made the switch to real-time.

Global hybrid cloud infrastructures make it all the much harder to protect data. Organizations are looking to AI-based approaches that give them insights to support data sovereignty.

Data democratization is about giving everyone within an organization access to all of its data, regardless of what role that person has or what they might be trying to understand.

In contrast to specialist AIs, DeepMind based Gato on a transformer neural network architecture, which is similar to a large language model.