As companies move from PoCs (proof-of-concept) to pilots and into full production roll-outs, companies test and validate many different technologies in the IoT stack and learn valuable lessons along the way:
- manual processes should be eliminated wherever possible
- extracting real business value from raw IoT data is hard
- integrations and workflows are cumbersome to build and maintain between platforms, backends, and enterprise applications
- building applications and services is more difficult than anticipated
Often times, a technology choice that seemed good enough in the early stages of an IoT project no longer stands the test of scale and complexity growth in production environments. Other times, as device data starts to stream, companies realise that only a small fraction of it is actually used, raising difficult questions with regards to the actual business value of the IoT solution.
A comprehensive guide to everything you need to know about automation software for IoT application development
In order to make better use of IoT data, to ensure that all stakeholders gain access to it and to abstract away IoT system complexities, enterprises are choosing to rely on three technologies – automation, orchestration, and intelligent APIs – to ensure efficient, secure and cost-effective IoT deployment and ongoing solution management.
In this recently published whitepaper, Leading IoT analyst firm MachNation discusses these three technologies and presents two use cases describing how they aid in development, deployment, and operation of typical enterprise-grade IoT solutions.