Store Sensor Data? No, Process in Real-Time! - ERP Spain.com - España y América Latina

Let’s talk about IoT & challenge some given truths about the value of stored data. It has proven hard for most companies that are not digital natives, to capitalize on data lakes. Most product OEMs, who are & will be the frontrunners of IoT, are no such actors. The harsh reality is that managing customer data comes at a huge risk, responsibility & cost. Data integrity is one reason for us, Ekkono, to technically approach this from the edge. By enabling real-time processing of the data on the device, with no human intervention, & only sending insights to the cloud, we increase integrity while decreasing risk. At the same time, this enables OEMs to develop smart features onboard their products to make them more intuitive, predictable, sustainable, & personalized by accommodating the place & purpose they are used for. Leveraging sensor data to develop automated, smart features is a great way to capitalize not just on data, but also on domain expertise. This way product companies in different verticals like industrial, automotive, energy & real estate can do more of what they do best & do it globally by leveraging new technology like sensors, connectivity & Edge Machine Learning. So, let’s talk about how you can augment your cloud & connectivity strategies with Edge Machine Learning that makes your products smart, self-learning & predictive. • Processing data in real-time is a game changer – learning what’s normal for an individual unit, to predict what will happen & detect when something deviates from what is expected to happen. • Collecting data comes with big responsibility. Don’t collect data unless you have a really good reason to do so. • You can make money on this, while at the same time helping the environment by running every single one of your products in an optimal & sustainable way. • Sensor data is the key to the true potential of IoT. More specifically, it spells Automation. But you don’t need a big data lake for this.