How slower network speeds can benefit big data

CIOs and big data planners need to put on their financial hats and think about the cost of data transport

Data Analysis for Business and Finance Concept

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There isn’t a company or a communications provider that isn’t thinking about the importance of 5G networks, which promise low latency and data transfer speeds that can be as much as 100 times faster than their 4G network counterparts. The benefit of these   high- speed networks for big data payloads goes without saying, —but there are also cases where paying the extra money for 5G or even 4G capability doesn’t make sense, even with big data.

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Capitalizing on the benefits that slower data transport such as 2G or even 0G networks can bring to the world of Internet of Things (IoT) are companies like Sigfox, which offers a global “slow G” communications network for operators in the logistics industry.

“Our focus is on asset tracking,” said Ajay Rane, vice president of Sigfox global business development. “Companies often find improved returns on investment (ROI) for the assets they are tracking when they can reduce the cost of the communications they are paying for.”

Rane cited the example of trucks transporting apples.

“The apples might be worth $50 to $100 per pallet,” he said. “Companies can ask themselves if it is worth it to have high-power communications for their networks, given the relatively low value of the cargo. In these cases, there is an advantage to using communications with speeds at the 2G or 0-G level, because it is significantly less expensive, and you can get to ROI faster.”

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Here is a case in point: A large tire manufacturer wants to track its containers that various third-party logistics (3PL) companies are picking up and delivering to stores.  The goal is to determine the best route for each container, and the strategy is to track the routes of each 3PL and determine which 3PL is the best delivery and cost choice for each route.

In this case, IoT big data is tracked, but the incoming data doesn’t need to be real-time or near real-time–it just has to be gathered for the purposes of analytics. The decision in this case is to use 2G data transfer speeds because the data doesn’t need to be delivered in real time. There is also substantial cost savings and ROI that can be more rapidly achieved.

Use cases like this can be applied to other big data processing at less cost, but are enough companies doing it?

Network, bandwidth, and data transfer speeds should be an integral part of big data planning, but as companies grapple with getting the right types of data, developing business-operative analytics and transforming their businesses, network considerations can often assume a subordinate position. As a result, the default can be to run the data over a 4G network—when the ROI on the communications may not warrant it.

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“There are many company assets that may not offer the value to warrant an expensive deployment of a 4G or higher network,” Rane said. “A basic chipset for these networks might go for as high as $100. For a 2G network, the cost is more like $20.”

This is why CIOs and big data planners need to put on their financial hats and think about data transport as much as they consider the mechanics of gathering the right types of data and delivering impactful analytics. They will be able to deliver the best big data analytics results and value for business decision-making—and also the best results for the bottom line.

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