Articles

Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the critical path and, in many enterprise-scale settings, forgoes hybrid complexity and multi-cloud risks. Nevertheless, slack in system designs does exist; financial institutions enable market functionality—trading, clearing/best execution—despite potentially being able to meet such sets with lower service levels than other verticals. A cloud multi-account structure for sensitive data, for example, naturally limits exposure when combined with observed risk. Fulfilling predictions of elasticity during periods of high demand usually requires support from a dedicated environment (or environments) located nearer to the operations. Components can consequently be allocated on a per-account basis or maintained as shared sink systems to which the dedicated streams write. The automation code can similarly be targeted for dedicated accounts, avoiding the resource constraints that beset such operations during industry events like emergency triage/contact desking.

This work details how the integration of cloud computing and advanced data engineering can innovate and reshape patient care and digital infrastructure. In the healthcare sector, cloud services offer the necessary support to generate digitally-oriented services and service kits. These services can contain high levels of availability, low levels of latency, and on-demand scaling capabilities, while following the strictest data protection laws and regulations. On the other hand, these services can be combined with data engineering techniques to construct an ecosystem that enhances and adds an optimized data layer on any cloud environment. This ecosystem includes technologies to acquire, process, and manage healthcare data while respecting all regulatory obligations and institutions and can be part of a comprehensive digitalization strategy. The objective is to augment the healthcare services that the industry offers by leveraging healthcare data and AI technologies. Designed services, processes, and technologies can be described either as industry-agnostic services or healthcare-specific services that process and manage electronic healthcare records (EHR). Industry-agnostic services offer a set of tools and methodologies to conduct optimized data experiments. The goal is to exploit any variety, velocity, volume, and veracity of medical data. Healthcare-specific services offer a set of tools and methodologies to connect to any common EHR vendor in a privacy-preserving manner. Participating companies are thus able to hold, share, and make use of healthcare data in real-time. The proposed architecture can be transformative for the healthcare industry, opening up and facilitating experimentation on new and scalable service models. The transition to a more digital health approach would help overcome the limits encountered in traditional settings. Limitations in the availability of healthcare facilities and healthcare professionals have underpinned the increasing share of telemedicine in the care process. However, the record-keeping of the patients that undergo care outside of traditional healthcare facilities is often missing and can severely influence the continuity of treatment. Identifying new methods to implement disease prevention and early intervention processes is crucial to avoid more extensive treatment and to support those on multiple line therapies. For chronic patients, having a service available that monitors the state of health and intervenes when parameters go off the wanted range is crucial. However, the same patients are the most under the influence of the decision of care providers; a second opinion might be given remotely which the patient can access at any time on-demand. To address these different kinds of services, an ecosystem composed of a dictionary's worth data layer is outlined, able to live and operate seamlessly in any cloud environment. This future work's envisioned outcome is the rapid evolution and re-definition of the European healthcare landscape.