Six steps to prepare for a 5G IoT future

Gartner predicts that by 2023, there will be 49 million 5G IoT endpoint devices installed, yet today, most companies have yet to realize what this means for their data systems. As the promise of 5G continues to drive massive growth in the IoT, enterprises must build systems to support the data created by all these connected devices.

Building these systems requires a new approach to database design. The approaches we use today simply cannot handle the sheer volume of data or unlock its full value.

[[316690]]

What do you need to do now to prepare your data systems? Here are six steps.

Make sure your data modeling approach is appropriate for your IoT deployment

Relational data models aren't going away anytime soon, but they weren't designed to meet the needs of IoT. Time series data models are better suited for managing IoT datasets, where events must be written based on time and then analyzed based on when the events occurred. This type of database provides better performance for IoT applications that ingest and use time series data. IoT devices need to do this, so adding a time series database model sets up a data foundation that can support them.

Deploy systems to view data in real time

Connected devices are constantly generating data that must be sent and received. It also often needs to be done quickly, which means you need the ability to see the data in real time. The best approach is to add streaming data to support IoT applications. For example, sensor data can be streamed for analysis and any required real-time response. In a medical setting, a patient can wear a heart monitor at home that sends a signal to a medical provider and alerts the provider if the heart rhythm changes. Real-time sensor and data streaming can be used to protect people or cargo from potential hazards. Only a streaming architecture that supports input from multiple data sources simultaneously can provide this capability.

Keep only the data you need

While IoT will generate a lot of data, some of it will quickly lose its usefulness and therefore does not need to be retained. For example, useful data collected during a project may not need to be retained after the project is completed. Storing unnecessary data is not only costly but also consumes resources. IoT data will need to be assessed for its value and relevance and assigned to the appropriate retention level. You need a database that supports data tiering capabilities, which can store data that has lost its relevance in different tiers to reduce storage costs. When appropriate, this data can be moved to long-term storage or deleted.

Scale Planning

More and more businesses are turning to hybrid cloud to take advantage of the cost benefits of public cloud while still retaining control over their future. As data volumes grow, IoT will require an ability to scale, and hybrid cloud can improve IoT performance by bringing data processing closer to where the data is created, while still managing it in a centralized repository.

No one can really predict how the increase in IoT devices will truly impact data volumes, but we do know that being able to scale as needed will ensure that businesses can keep pace with demand. Being able to scale data horizontally is also more cost-effective, and at this point, hybrid cloud is the best solution for an uncertain data future.

Automated data replication

Replicating data ensures that you don’t lose data, but it can be challenging from an operational perspective as well as for compliance in certain industries. Data replication transfers data between nodes. By automating this process, IoT edge devices can easily replicate their data to a central repository. Using the same approach for data on all nodes, from individual devices to edge data centers to central databases, simplifies this process further and ensures that applications run the same way on all components.

Add analysis

Finally, IoT will require strong analytics capabilities. The more data you have, the more you need to exploit the value of that data. Analytics help you discover usage patterns and identify weaknesses in devices. Real-time analytics tools integrated with your data systems will help you leverage IoT data in a 5G world.

Taking these six steps will lay a solid foundation for the fast-approaching 5G IoT future. By ensuring your data systems are compatible and support 5G and the data created and analyzed by IoT devices, your business will be able to take advantage of the benefits of IoT and deliver the experiences that today’s modern customers expect.