Cutumba

The IoT market is projected to realize exponential device growth over the next decade. In this early day of device expansion, manufacturers and service providers are using a combination of in-house and off-the-shelf technologies to connect their devices to provide a modicum of data. However, as the volume of these devices begins to explode, device makers are beginning to realize that managing and understanding their IoT systems and associated components is becoming a nightmare. IoT is complex, with each end device having multiple components, ranging from device SW to edge SW, from cloud connectivity to high scale event processing, from rules engines to device shadows, and from client connectivity to device-client interaction. Yet understanding the pulse of these systems and their device health is very challenging because traditional analytics pipelines tend to be quite convoluted and overly focused on business function. As such, operational insight has always been an afterthought. IoT’s needs are unique insomuch as they require analysis of streaming and non-streaming data and the data science required to provide this analysis must be custom to each system’s specific schema. Cutumba solves this challenge with Signal Quotient, a semantically-enabled data science platform designed from the ground up for IoT operational needs. This advanced solution incorporates pre-developed and extensible data science models, out of the box, packaged with ad-hoc query analysis and data sharing capabilities to keep the device maker up to date about the health of their systems. With Signal Quotient, they now know where their issues are concentrated and are provided recommendations to resolve them.