September 2017 Summaries

The Industrial Internet of Things (IIoT) is a network of connected devices that can monitor, collect, exchange, analyze, and deliver valuable insights. Industrial companies are adopting IIoT to drive operational efficiency, predict failures, and innovate across ecosystems. However, the power of data in transforming industries is hindered by structural, commercial, and technical barriers. The 1% problem, scale, and shelf life of data pose challenges for transactional and decision analytics systems. Companies are investing in new systems that can generate, capture, store, retrieve, process massive data sets from disparate sources, and turn data into operational insight. These systems require a datastore that can scale infinitely, perform in milliseconds, and be cost-effective.

The Industrial Internet of Things (IIoT) is a network of devices connected by communications technologies that enable systems to monitor, collect, analyze, and deliver valuable insights to drive smarter business decisions. IIoT adoption aims to achieve three distinct outcomes: operational efficiency, predictive maintenance, and digital innovation. However, the power of data in IIoT is hindered by structural, commercial, and technical barriers, including the 1% problem, scale constraints, and shelf life limitations. To overcome these challenges, companies are investing in systems that can generate, capture, store, retrieve, and process massive data sets, turning it into operational insight. These systems require datastore solutions that can scale infinitely, perform in milliseconds, and be cheap, enabling transactional analytics at the edge of the network.