Internet of Things (IoT) architectures will lead to significant distribution and diversification of data, which will impact on analytics, stakeholders, information managers and infrastructure, says IT research and advisory firm Gartner research director Nick Heudecker.
The IoT entails the processing and massive distribution of data. Data will be produced, collected and stored in multiple locations, depending on the nature, goals and use of the IoT architecture, he explains.
Analytics are highly distributed in an IoT architecture; therefore, distributed management and data use must become the norm for information managers.
“Companies must plan for disaggregation and resilience. Workloads must be able to be divided into components that can operate anywhere. This means that the implementation of existing business logic for processing data and the current choices of data-management infrastructure tools might not be suitable for IoT requirements, driving organisations to redesign or modernise those capabilities,” he says.
Data produced by devices might be stored on the device in intermediate locations, in a centralised on-premise repository or in the cloud. Processing such data might happen in any of those locations. Many devices will be powerful enough to perform sophisticated computation on the data they generate, and/or house and process data locally for autonomous behaviour.
IoT solutions will generally involve a com-bination of platforms, with data and processes on that data being located ’on-device’ and in tradi- tional on-premise and cloud-based environments. It is, therefore, important to avoid forcing analytics and information management solutions into a monolithic or one-size-fits-all deployment model.
IoT architectures will often be the opposite of the monolithic model, thereby increasing the challenges of monitoring and managing distributed data and its consumption. As a result, information infrastructure capabilities that can be located and managed anywhere should be deployed, emphasises Heudecker.
Some IoT scenarios will rely on the highly centralised collection and processing of data in traditional on-premise environments or cloud-based repositories and compute platforms.
Organising and managing highly distributed data is a significant challenge. Ensuring that the distribution and consistency of business rules are applied to the data, and that these rules are monitored, add further complexity.
“The characteristics of IoT architectures mean that information management practitioners must swiftly become adept at managing many pieces of information over a wider and more diverse landscape of platforms than ever before,” concludes Heudecker.