IoT generates new data, enables the discovery of analytical insights, and requires technology investments-all of which would be rendered useless if they cannot produce real business outcomes. While enhanced visibility to operations from device data creates value, additional value can be achieved when companies leverage data science and machine learning to predict outcomes, anticipate changes, and optimize business processes accordingly. This predictive foresight creates competitive differentiation and breakout growth.
Therefore, companies need a compute platform that harnesses the cloud to optimize data processing at "the edge" of the network and at the core data center for optimal performance, costs, and value of analytics. Over time, as IoT initiatives become more sophisticated, companies may find increasing need for both depth of quality and immediacy, leading toward more powerful compute resources moving to the edge.
2. An always-on and stable network
Reliable, extensible connectivity is the foundation for enabling a robust IoT platform. In some cases, companies may be gathering data to physically control "things" real-time, such as equipment within a power plant (e.g., certain readings may reveal the need to adjust settings on a device). Such precise data analysis may require compute power closer to the edge of the convergence between the IT systems and devices to reduce the inherent latency introduced by sending information back to a data center or cloud environment. The use of data aggregation and gateways at the edge is a common approach in IoT environments as it can compile and filter out data to alleviate bandwidth challenges.
3. End-to-end encrypted security
While IoT can create tremendous value, it also creates new security vulnerabilities and increases the threat of breaches for companies across devices, users, applications, data, and networks. Security complexity and risk factors further increase with IoT because the scale of physical assets, the amount of data and the remote proximity to devices stretches existing security systems. Additionally, the use of a mix of legacy and new systems may create gaps for attacks.
Cyber-security must be proactively managed end-to-end from the device, edge, network, and core. Connecting a multitude of new endpoints to a variety of different networks yields an expanded attack surface area, and therefore requires security resources at the edge of the network.
4. Open and connected ecosystems
High-quality ecosystems that promote interoperable products and services create value for everyone, most importantly the customers that use them. This means being able to interact with the broadest possible ecosystem of business intelligence, visualization, predictive analytics & machine learning, data prep, ETL (extract, transform load), cloud, open source, security and other solutions.
However, creating an ecosystem of connected solutions and technologies is not always easy. Interoperability issues can arise from disparate networks of sensors and devices. With the growing amounts of data online, information is often discarded or ignored, which prevents companies from getting the real value from data. Flexible storage capacity and a purpose-built analytics engine designed to handle large volumes of data are essential to capitalize on the potential of IoT data.
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