Why IoT Companies Are Turning to Intelligent Data Distribution

Three core issues—latency, efficiency, and scale—must be addressed in order to solve the distribution dilemma.
By Andréa Skov

The IoT market is maturing, and with that comes a realization that network-efficient, high-volume data streaming and messaging is critical for corporate applications and analytics. Simply put, companies using IoT devices must have solutions that increase reliability, and reduce bandwidth and infrastructure requirements. This equates to intelligent data distribution and management, in conjunction with an architecture designed to put the data as close to the end user as possible—whether that is a machine, a device or a person.

In addition, to lighten the load on the network, companies need to understand their data. This means the technology they employ must apply intelligence and only distribute what is relevant or what has changed, so that only smaller pieces of data are sent across congested networks.

When approaching IoT data distribution, you cannot do so in the same way you conduct mobile data distribution. You need a strategy for collecting all the data from "things" at scale over unreliable networks, the intelligence to only pass on what is relevant, resilience to cope with sometimes unreliable networks and connections, and efficiency so you are not exhausting bandwidth. In some cases, data is sent to a warehouse for storage in the event of auditing or reporting, but some of the data must to go through your analytics engine, AI systems or real-time tools—for example, for fraud prevention or risk detection for processing.

Once processed, your data then needs to be distributed. You need to understand, at speed, what needs to be handled, then send it for processing and distribute it—whether the data is addressing the stoppage of a stolen credit card, telling first-responders to an accident that they need to change routes due to traffic congestion, or changing traffic light signals to reduce congestion.

The problem is that many data-communication technologies are messaging systems that blindly send large amounts of information back and forth. The specific demands of the IoT preclude effective use of general-purpose data-transmission technology solutions that work adequately for less demanding operational environments, such as chat or social-media platforms.

Therefore, intelligent data distribution is one answer. If you use technology that is both message-size-efficient and data-aware, you can intelligently, automatically and optimally manage data transmission and remove out-of-date and/or redundant data. This can deliver up to 90 percent data optimization across the Internet—which, in turn, translates to a substantial reduction in bandwidth and infrastructure requirements, and assures minimal latency for data transport.

If systems can understand data and only distribute what is important, at the application level, this is more powerful than any amount of hardware thrown at the problem.

Andréa Skov is an international marketing, sales, and operations executive with a successful 25-year career in strategic planning and innovative tactical execution to ramp high tech companies from inception through liquidity events. She is currently CMO of Push Technology Ltd. Her previous positions include chief marketing officer at Teneros (acquired by Ongoing Operations), CMO of All Covered (acquired by Konica/Minolta), president and founder of CoolSpeak (acquired by SunCorp Technologies) and CMO of ICVerify (acquired by CyberCash). Andréa holds BS and MS degrees in physics from Northeastern University.

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