It’s undeniable that IoT devices are increasing and there is no end in sight for the data they are producing. Because of this, the notion of collecting information from sensors and bringing it into one central computing station is no longer scalable or efficient enough for the requirements of today’s business. With so many devices producing data, a traditional approach to analytics won’t work, but there is a solution – execute analytics in distributed servers on-premises and on the edge devices themselves.
Gartner supports this notion and they predict that instead of creating a new architecture, cloud computing and edge computing will evolve as complementary models with cloud services being managed as a centralized service that’s executed not only on centralized servers, but in distributed servers on-premises and on the edge devices themselves.
It’s predicted that through 2028, the embedding of sensor storage, computing and advance AI capabilities in edge devices will steadily increase, and 75% of enterprise-generated data will be created and processed outside of centralized cloud and data centers, and relocated to the edge by 2022.
Data and analytics leaders should consider Executing Analytics in the Distributed Services when:
These disruptive trends in the industry are leading to a new mentality where data and analytics is the enabler to the overall business strategy, making it critical to understand and experiment with them before they become mainstream. If they are not implemented, new business opportunities could be missed. Empowered Edge: Executing Analytics in the Distributed Services isn’t the only trend we are seeing this year.
You’re one step closer to enabling an analytics-driven organization. Discover the 9 Data & Analytics Trends for 2019.