Systems | Development | Analytics | API | Testing

Data quality is fairly simple nomenclature to describe the state of the data being processed, analyzed, fed into AI, and more. But this modest little term belies an incredibly critical and complicated reality: that enterprises require the highest level of data quality possible in order to do everything from developing product and business strategies, and engaging with customers, to predicting the weather and finding the fastest delivery routes.

Remember way back around 2016, when “IoT” was just entering the lexicon? The technology behind the “Internet of things” was starting to be used across industries. In the energy space, for example, companies used it to capture data being sent from tens of thousands of sensors from various equipment, like inverters, controllers, anemometers (wind speed detectors), cloud-watching cameras, and more.

The usage of resources is one of the critical factors in IoT contexts; it is common to observe that devices can suddenly disconnect when their available resources are exceeded; monitoring, however, can be worse due to the additional resource consumption required for such tracking.

For the newest instalment in our series of interviews asking leading technology specialists about their achievements in their field, we’ve welcomed Tim Panagos, CTO and Co-founder of IoT data startup Microshare. Tim is a technology executive with over twenty years of experience in enterprise software. Tim was most recently Chief Architect of Accenture’s global Business Process Management (BPM) practice, where he led software architecture innovation.

Hitachi Vantara today announced the new Lumada Industrial DataOps portfolio with core IIoT platform framework capabilities. With this release, we are making it easier for organizations to take advantage of real-time insights and outcomes that can make critical operations more predictable and manageable. One of the highlights of this release is the introduction of IIoT Core software, which includes digital twins, ML (machine learning) service, and user interface components.

More than a decade into the Internet of Things (IoT) era, the immense potential of IoT is becoming real. We’re moving from proof of concepts and pilots to projects at scale. What’s become increasingly clear is the vast complexity of deploying IoT solutions at scale and the necessity to do so to become a data-driven business.

If your business is in the process of digital transformation, IoT technology may be factoring into your plans. IoT gives organizations across industries new opportunities to foster a more direct connection with customers. It lets them collect new data, turn that data into insights, and then turn insights into action. IoT has become so prevalent that companies in most industries can’t afford to put off adopting it.

In the age of a new normal, remote monitoring and control have become a necessity across the enterprise. The prominence of IoT extends beyond its traditional purpose of sense and integration, evolving to complete end-to-end Enterprise Digital applications that represent physical assets, processes, and environment as a replica in a virtual representation.