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Managing Massive Iot Data Workloads in 2022
By Sam Dillard, Senior Product Manager at InfluxData
Digital information is growing at a staggering rate, with reports citing 90 percent of data in the world today being created in the last two years. Moreover, the IDC predicts the world will be fitted with 41.6 billion IoT devices by 2025… from which 79.4 zettabytes of data will be transmitted. And in 150 years from now, the number of digital bits will exceed the number of all atoms on Earth. The recent and continued ballooning of data is a good thing for us data nerds, but it comes with expanding complications, too.
Hundreds of vendors and thousands of individually contributing community members are responsible for the instrumentation of the world. This is leaving data companies with increasing pressure to manage these massive loads of IoT data being constantly produced.
The field of data engineering is centered around getting data from the point of instrumentation into the hands of data scientists and analysts in a form they can use effectively. So what exactly does that mean for us, and how will that impact our decision making in the next year and beyond? Significant volumes of data come with new challenges, but also with exciting new solutions.
IoT interoperability remains IT’s next big hurdle: As IoT extends into every facet of our lives, operators’ and data architects’ big challenge is delivering interoperability of IoT data – collecting it from disparate systems, sensors, devices and applications, and making it work together to derive insights from it. Significant barriers prevent organizations from achieving data exchange between components of infrastructure – legacy systems and siloed data streams are the major roadblocks. Next year organizations will tackle this problem by adopting IoT data platforms that interoperate with a broad set of solutions: data collecting, stream processing, visualization, alerting, machine learning and AI frameworks. Pairing these solutions together, developers will be able to face interoperability challenges head-on to drive better data insights.
IoT ubiquity pushes organizations toward intelligent storage techniques: The rise in IoT requires organizations to treat this data according to its properties. It has high volume, it has massive storage requirements, and each data point has a “half life”, meaning it loses business value with age. In the upcoming year, organizations will need to unlearn their previous approaches to traditional data storage and adopt principles that accommodate the nuanced nature of IoT data. Organizations will quickly realize the benefits of intelligent storage techniques, including the ability to predict issues and make changes that proactively intercept the problems. This will improve performance and efficiency, and optimize workloads.
Specialized IoT platforms unlock IoT value: All IoT devices generate time-stamped (or time series) data. The explosion of this type of data, fueled by the need for more analytics, has accelerated the demand for specialized IoT platforms. By 2025, there’s projected to be 60 billion connected devices around the world, the vast majority of which will be connected to IoT platforms. Storing this data is the first hurdle; making it all sync together seamlessly is the challenge that organizations face next year as IoT deployments continue to scale at a rapid pace. As companies face massive volumes of data, they will adopt specialized IoT platforms that can not only keep up with the data being produced, but can also manage and offer better visibility and real-time monitoring for the IoT data and ultimately provide more value.
To sum up
IoT is a constantly expanding and evolving field, with data growing every day. Interoperability will remain a hurdle for IoT, but can be met by adopting IoT data platforms that interoperate with a broad set of solutions. These data platforms will also need to be equipped for intelligent storage techniques to optimize massive workloads. Finally, specialized platforms will continue to take center stage, pulling all the IoT data together and helping organizations unlock more value from the data produced.
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ABOUT THE AUTHOR
Sam Dillard | Senior Product Manager, InfluxData
Sam Dillard is a Senior Product Manager at InfluxData. He is passionate about gauging future market needs and building software to get ahead of them. Sam has a BS in Economics from Santa Clara University.
