CIOs and big data planners need to put on their financial hats and think
about the cost of data transport.
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.
SEE: Special report: How to
win with prescriptive analytics (free PDF) (TechRepublic)
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."
SEE: How disaster relief
workers are using data analytics to support and measure their efforts (free
PDF) (TechRepublic)
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.
SEE: Big data management
tips (free PDF) (TechRepublic)
"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.
No comments:
Post a Comment