Analysis And Optimization Design Of Big Data Platform Of Jilin Province Rural Credit Bank

In recent years,in the context of a new round of technological development and industrial transformation,most commercial banks have used information system construction to deeply integrate financial services with emerging technologies such as big data and cloud computing,providing continuous innovation impetus for the vigorous development of banks’ operations and businesses.Jilin Rural Credit Union(hereinafter referred to as "Jilin Rural Credit Union")is the largest local financial institution in Jilin Province.With the rapid development of business,data accumulation is increasing.In order to solve the problem of insufficient data storage and computing capacity throughout the bank,Jilin Rural Credit established a big data platform based on Hadoop architecture in 2019.Through the big data platform,Jilin Rural Credit established a unified reporting,regulatory submission,risk control,asset monitoring,and other data mart to meet the daily management needs of Jilin Rural Credit.As the big data platform system gradually participates in the management and operation of Jilin Rural Credit,some problems have also arisen in the use of the big data platform,mainly including: long data extraction cycle and slow response time for business personnel;Business personnel have a single way of obtaining data,weak data service capabilities,and low data utilization;There is a lack of data asset management,and business personnel cannot accurately grasp the actual operating level of Jilin Rural Credit through data.This article analyzes the problems encountered in the operation and management of Jilin Rural Credit Big Data Platform,and finds that the existing problems of Jilin Rural Credit Big Data Platform include: insufficient cluster resource planning capabilities,lack of unified data processing processes,lack of data application architecture,incomplete data organization architecture,and lack of data management systems.In order to solve the existing problems of the Jilin Rural Credit Big Data Platform,this article provides an optimized design plan for the Jilin Rural Credit Big Data Platform in terms of cluster resource management and control,unified development process,data team construction,and missing system establishment.Through the structured system analysis method,the existing application architecture of the big data platform is designed as a whole,and an optimized design scheme for data collection,data model,unified scheduling,unified data development,unified data service,and unified monitoring module is proposed to improve the data application capability of Jilin Rural Credit.Ensure the implementation of the optimized design scheme for the big data platform by establishing communication and coordination,detail control,and resource assurance mechanisms.The implementation of the optimization design scheme for the big data platform can help Jilin Rural Credit to break through data silos,unify the caliber of data indicators,form data assets,improve the quality and efficiency of data processing,and improve data service capabilities.Through the optimization of the big data platform,data services can be better integrated into the business process of Jilin Rural Credit,assisting the management to quickly and effectively analyze and make decisions,thereby helping Jilin Rural Credit achieve excellent operations and improve the comprehensive competitiveness of the enterprise.Other small and medium-sized banks in China may also encounter problems encountered by Jilin Rural Credit in the construction of big data platforms.The optimized design scheme of big data platforms precipitated by this study has certain reference value for the exploration of big data applications in these banks.