Connected Manufacturing is at a turning point. Analytics, machine learning, and artificial intelligence are reshaping the manufacturing landscape.

However, in order to capitalize on this fundamental shift, manufacturers need the ability to ingest, process, store, and analyze all types of data (structured, unstructured, and semi structured data) regardless of where it lands—at the edge, on the factory floor, in any public cloud, or in a hybrid cloud.

Today’s manufacturers face limitations addressing the stressful complexities of digitalization. Much of these limitations are due to the rapid evolution of new, connected data sources and the massive volume of data spawn out.

Real-time data is growing 50% faster than latent or static data forms coming into the forefront of manufacturing use cases because they enable real-time insight and more importantly autonomous decision making.

Manufacturing organizations will require an up-to-date data infrastructure that reduces data management expenses, accommodates the sheer volume and diversity of IoT data, handles the intricacies of real-time data processing, and possesses distinctive features tailored for hybrid and multi-cloud environments. This platform should also effectively address critical manufacturing use cases, offer comprehensive security and governance from the edge to AI, and be built upon an open, continually evolving architectural foundation.