Industrial IOT :
The Industry 4.0 revolution, powered by IoT, is driving increasing focus on connected factories, assets, and industrial ecosystems. Data generated by connected devices has the potential to provide your business with crucial insights, such as how your assets are performing in real time, how agile your supply chain is, and how your products are being used. It can even predict when and how something might break. Oghatron’s data management and analytics platform can help process sensor and machine data from connected assets, in real time, and help predict key outcomes, ensuring you are always ahead of the curve.With 30+ billion things connected, IoT will drive an explosion of data that will need to be processed, stored, managed, analyzed, and served (in some cases in real time) to drive business value. IoT will generate far greater volume and variety of data than most information leaders are currently familiar with—requiring a modernization of information infrastructure to realize value.
Some of the key characteristics of IoT data include:
- Massive volumes of intermittent data streams-amounting to millions of events per minute
- Predominantly time-series data
- May come in streams (real-time) or batches
- Generated from a variety of data sources-from sensor readings of temperature and pressure to live video streams
- Can include diverse data structures and schemas based on the sources
- May become perishable (value of data decreases over time)
Given this complexity and variety of IoT data, organizations must fundamentally re-think their data management strategy—transitioning to a platform that is optimized for the scale and complexity that IoT presents. More importantly, the real value from IoT can only be exploited if organizations have the ability to combine and correlate these sensor data streams with data from other internal and external data sources; and, in some cases, even combining this with data from other IoT ecosystems.
To realize the full potential from IoT, and extract actionable intelligence, organizations and underlying architectures will need to evolve. In fact, the success of IoT deployments will depend on the ability of organizations to gain insights out of all this fast moving, high-volume data.