Cloud-based infrastructure as the backbone of scalable financial intelligence platforms

Cloud-based Infrastructure as the Backbone of Scalable Financial Intelligence Platforms. The history and trends of cloud computing are analyzed, including development motives, a reference architecture, and fast growing AI centers. Cloud-based vendors face unsustainable maintenance and operational costs as their cloud services scale, creating a dilemma for software vendors. Many data-centric software vendors now provide their products on public cloud infrastructures. The challenges of cloud resource provisioning are analyzed and classified into four levels, including long-term trends, medium-term demand, short-term demand, and real-time adaptation. The Coarse grid-based resource allocation algorithm is designed to make efficient cloud resource allocation decisions at the fine allocation level. The algorithm and access patterns are exposed to cloud resource allocation decision makers.

Cloud computing is a large-scale distributed computing and storage integrated system composed of massive physical resources, including data centers, servers, storage devices, and networks. Cloud computing promises its users with on-demand, elastic, cost-effective, reliable, orderly, location-independent, multi-tenancy, pay-per-use computing resources and associated services. Financial social media has attracted extensive attention in academia and the industry. Users share financial information with various forms by posting, reviewing, liking, or forwarding. The experimental results of the pilot test of more than 700 investors show that investors' financial intelligence is generally low with great hierarchical aggregation, and the financial intelligence level has been improved and be more rational via investment experience. The development of financial social media has led to data explosion in the finance domain, causing great pressure on corporate data processing and analysis. However, many information systems and platforms of financial institutions work in silos with isolated data.The further popularization of cloud storage has long been hampered by concerns for safety and unawareness of its necessity. Subsequently, in order to overcome these two barriers, a modularized infrastructure of cloud computing technique-based financial intelligence platforms is established. Then, 13 types of financial intelligence platforms are coded using the modularized infrastructure to broaden the financial cloud scope, and the methodology for determining the appropriate cloud computing scheme is proposed to eliminate the concerns for safety and privacy. In short, the goal of this effort is to construct a scalable financial intelligence platform for cloud computing technique and data manipulation. Much effort is contributed to achieve this goal. It is expected that the proposal of data powered intelligence platforms will promote further exchanges on the furnishing of cloud computing or big data based financial intelligence platforms.