IoT and Data Management: Channelizing Business Efficiency, Mitigating Complexities
The Internet of Things (IoT) is known for catalysing business growth. IoT and analytics platforms are transforming businesses with their more productive capabilities to gain quality insights through connected data-driven solutions. Data is streaming into business systems from a plethora of internet of things sources such as sensors, appliances, smart personal devices, and industrial equipment. This increasing availability of IoT data needs a strategy to take full advantage out of it.
With a variety of devices deployed, it may be impossible for a business to move the data into the data center without investing heavily in external networking. Also, in many instances, the value of the data may not be best served by storing everything. Another point to consider is the timely processing of data. IoT devices may need to make local processing decisions quickly and not tolerate the latency of analyzing and transmitting data into a core data center for processing to occur.
Effectively analyzing and ingesting data stream can inform the management of operational processes and pinpoint ways to enhance them. Pulling data from multiple data streams is beneficial and enables a holistic perspective on myriad business activities. IoT data sources provide a wealth of information that can be integrated into predictive models to support decision making. The data management architecture must be able to accommodate the volume of and variety of data available.
Filtering is useful to speed automated streaming analytics, but the analytical models need to be developed using historical data. The body of accumulated data forms a system of record that can be explored by data analysts and be used to build other predictive models in search of new insights.
When attempting to use IoT data from different sources, consider the above aspects as an effective IoT data management strategy — following the same before deployment keeps the organization away from drowning in the flood of data.