As hyper-scalers brace for the next waves of data generated by Internet of Things (IoT) deployments and wider 5G network pipes, data warehouse vendors are partnering with the telecommunications industry looking to upgrade their data analytics and machine learning capabilities.
Yellowbrick Data, the SQL data warehouse vendor, said this week it will collaborate with Digital Outcomes Now, an industry group made up of data analytics, mobile and cyber security experts. The partnership aims to help the global telecom industry “convert their massive data volumes into positive outcomes,” the partners said Thursday (March 19).
As it ramps up 5G initiatives, the digital group said it will use Yellowbrick’s data analytics platform for emerging applications such as distributed analytics at the network core and edge as well as in hybrid cloud deployments. Yellowbrick’s platform is designed for data warehouse volumes up to several petabytes, a capability that would allow Digital Outcome Now’s members to better utilize the capabilities of 5G wireless networks, CEO John Gillespie said.
The group also cited Yellowbrick’s 20-fold reduction in rack space compared with traditional data analytics platforms.
Telecom providers have already made hefty investments 5G networking gear and storage platforms. This week’s partnership reflects healthy spending forecasts as 5G networks are deployed. For example, ABI Research estimates that IoT data and analytics services revenues surpassed $23.6 billion in 2019. Revenues are forecast to reach $118.4 billion by 2026 as health care, transportation and other sectors embrace data and analytics services, the market tracker said in a report released this week.
Meanwhile, the combination of 5G, IoT data, analytics and mega-storage is expected to provide new analytics capabilities for AI. In one example, 5G’s ability to support an estimated 1 million concurrent edge devices per square kilometer would provide the network scaling required to collect huge amounts of data from 5G-equipped devices.
“As 5G networks begin to flood data streams and lakes everywhere with fresh data from devices, AI application developers and data scientists will be able to build more sophisticated analytics and machine learning models for real-time applications in IoT, mobility, industrial automation, smart cities, and countless other use cases,” industry analyst James Kobielus wrote in Datanami last December.
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