Top experts and skills needed for IoT success
Select experts and skills specific to IoT
Organizations that need to provide specialized products and services for their customers at a lower cost and better performance must build their own IoT deployment. However, building will cost more upfront and require more expertise, as executives must assemble IoT developers, systems integrators, data scientists, engineers and tech leaders with change management skills. The ideal team — whether hired internally or externally — must cover all aspects of an IoT initiative, including hardware, software, networking, data management, analytics, control systems and team management to succeed.
If organizations are building their IoT deployment in-house, they will need well-versed IoT developers who are capable of designing and testing the hardware, communications protocols, user interfaces and the application. IoT data aggregation and analysis is shifting from the cloud to the edge, making expertise in cloud and edge-based infrastructure essential. With the number of skills needed for IoT developers to build IoT initiatives, organizations will likely need more than one expert to fulfill the role. If IoT developers choose to use platforms to build out their IoT project, developers also must know how to use the chosen platform, such as IoT and cloud offerings from AWS, Azure or Google.
The value of IoT technology comes from the data that sensors and devices generate. IoT data scientists play the key role in ensuring the quality of data analysis and predictive systems in IoT deployments. They can also address the widespread device distribution and complicated networking infrastructure. The data IoT devices create at the edge must meet different data management and analytics requirements than the cloud, including preprocessing data, integrating multiple sensor inputs, establishing machine learning and AI models at the edge and functioning in real time. Organizations must also determine what data needs to stay at the edge and what data should be sent to the cloud or data center. The IoT edge architecture requires data scientists who understand signal processing, gateway layers, edge analytics and blockchain. Although edge computing has much in common with cloud computing, and both call for machine learning, IoT technology typically demands real-time response and expert skills not necessary for cloud computing.