Hermes Logistics Technologies is working with the IT University of Copenhagen, Denmark, and dnata Australia to explore new machine learning models for business analytics.
The AI of HLT will run the algorithms from dnata and captures and stores all of dnata’s Hermes New Generation (NG) Business Intelligence events. Machine learning of dnata helps to make predictive business process decisions based on efficiencies, costs, and new services.
Machine learning is a part of Hermes Logistics Technologies and data lakes are the sources of events and data, which are up to date and ready to inform and train AI models in the Hermes Cloud. Trained models of AI will create predictive functions for dnata and help an already competitive cargo handling offering.
The ITU team, working with HLT, will create, test, and develop the predictive models over the coming months to explore the design of cloud-native enterprise machine learning solutions. The future of enterprise machine learning is by cloud providers, where any enterprise can incorporate data-driven predictions into their business processes.
Collaborating with Hermes Logistics Technologies and dnata is an opportunity to find the capabilities and limitations of cloud-based enterprise machine learning. dnata recently went live with HLT’s H5 Cargo Management System (CMS) at six airports in Australia which are Melbourne, Sydney, Adelaide, Darwin, Perth, and Brisbane.
dnata will be using predictive modeling to enhance cargo planning and operational processes. This data science not only benefits interaction with customer airlines, but it also helps to anticipate the demand patterns in advance for more logical operations. The dnata machine learning is part of HLT to deliver value-added services using Big Data analytics.
