The development of 5G technology is predicted to lead to more connected devices and more data being created by them. All that data will have to go somewhere, and managing the 5G data deluge will be essential. And how can companies plan ahead around all this data to make it useful?
The 5G standard – or IMT 2020 to use the official title from the International Telecoms Union – has to meet a set of standards. These revolve around the number of devices that 5G can support, the traffic levels that it can achieve, its energy efficiency, and connection density. For example, targets for the 5G standard include peak data rates of 20 gigabits per second (gbps), standard user experience data rates of between 100 megabits per second (mbps) and 1 gigabit per second (gbps), and support for a million devices per kilometre squared.
To put this into perspective, Netflix’s highest quality 4K streaming only requires a streaming data rate of 2mbps and uses 7 gigabytes (GB) of data an hour while 5G at its peak can deliver 2.5GB per second. All of these standard requirements will increase the sheer number of connections that can be supported on the network, as well as allowing those devices to share more data.
5G supports more devices and more use cases
In response, more companies are looking at deploying Internet of Things (IoT) projects over the next few years. The growth of IoT is due in part to smarter devices that can do more things, but also due to the connectivity that 5G can provide. According to Statista, the number of 5G connections is projected to grow to 1.1 billion by 2025. Developing this network will not be cheap – McKinsey estimates that network-related capital expenditures would go up by around 60 percent from 2020 through to 2025.
The potential rise in the number of devices will lead to more data being generated, adding traffic to the network and paying the operators back for their investment. However, like many things in life, the volume of data consumed will potentially expand to fill the pipes that are available. The performance improvement that 5G should deliver will make it possible to support more and different use cases over time as well. These use cases should help businesses create more value for themselves or their customers, and therefore pay for the infrastructure investments too. Services that would previously have been hampered by latency, such as gathering and using real-time information based on a device or a person’s precise location, will now be possible.
At the same time, this increase in bandwidth should support more in-depth data gathering. Rather than capturing a small set of data points from each device, the amount of information and data points used will go up significantly. For example, a supply chain or logistics company today may cover eight or ten data points today per parcel; in the future, the same parcel may generate twenty, thirty or forty data points. This means that devices will provide more information back to the business, based on 5G’s greater capacity and throughput for the same amount of energy used.
How IoT will depend on 5G and data
This increase in data will mean more infrastructure investment for the network operators. However, it should also lead to more investment around data for the companies implementing more IoT projects, too. All the data from these devices will have to be stored over time, in order to obtain value from it.
The opportunity to create value will come in two ways: through using the data at the time that it is created; and from looking at the data in aggregate for analytics. Using data in real-time will involve creating a pipeline for data to come in, be processed and used. These pipelines will tend to be based on streaming data, where data comes into the organisation and triggers a set of actions or responses based on its status.
Cloud, data and infrastructure
Running such databases can rapidly lead to a huge volume of data being stored. While it is possible for companies to build out their own data centres to support this infrastructure, cloud services are a natural fit for time-series data. Using services such as Amazon Web Services, Microsoft Azure or Google Cloud Platform to host the data can be a more cost-effective option (Microsoft has already partnered with AT&T to combine cloud service and 5G). However, while these cloud services can provide their own database offerings, they may not be the best option for time-series data and represent a potential to being locked into a specific provider.
For companies that want to maintain control over their data, and take advantage of cloud to reduce their costs, taking a hybrid or multi-cloud approach is a valuable alternative. Rather than putting all your data into one cloud provider’s service, running either a mix of internal IT and cloud, or multiple cloud services at the same time, can provide better performance and avoid lock-in at the same time.
Alongside this, hybrid and multi-cloud services can help companies take advantage of the benefits that each cloud provider uses to differentiate themselves. For example, if a cloud provider is particularly strong around AI and machine learning tools, then it may make sense to take advantage of these tools where it is appropriate. At the same time, the overall cost to store data may be cheaper on another cloud service provider. Taking a multi-cloud approach can help retain this flexibility and control over the economics of running IoT applications.
This distributed approach to data will become essential over time. As more IP-capable devices connect and 5G provides more bandwidth, companies will be able to gather more data around their activities. However, just gathering all this data will not be sufficient. Instead, companies will have to think through how they will manage this amount of data over time. They will also need to consider the need to track and have audit trails for all this data to ensure data compliance.
Dealing with the data deluge that 5G will cause will require planning, but 5G will also support companies in achieving new goals that were not possible previously. Effectively using the data that IoT devices running on 5G will create will rely on capturing data efficiently, analysing it in the right way, and deploying that data at the right points in time.
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