Use Cases
With rapid growth in Yinhua Fund's business data scale and business development, higher requirements were placed on the data warehouse system, mainly reflected in low development efficiency of the original Oracle data warehouse, high maintenance costs, single service form, relying on manpower increase to meet business needs, unclear data structure in core businesses like marketing, investment research, and anti-money laundering, and huge bottlenecks in big data computing and storage. There was an urgent need to meet business requirements for high-performance data processing, efficient data services, complex business calculations, massive data queries, metadata and data quality management. Against this business background, the company proposed building a fund data center platform in 2020.
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Through mature financial data center platform solutions, China Life AMP Asset Management Co.,Ltd reconstructed its data management and application system, established a new data warehouse model, and developed a new real-time data monitoring cockpit; comprehensively improved data processing efficiency, achieving dynamic monitoring and efficient application of data.
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The financial industry has high requirements for technology-driven business development. The data center platform assists financial groups in achieving more intelligent business decisions in the internet era, making enterprise strategy formulation more rational, and helping financial groups transform data assets into strategic assets and market competitiveness.
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Currently, with Guiyang Bank's rapid business development and business data sedimentation reaching a certain scale, to further enhance data service and data management capabilities, create a closed-loop model of business sedimentation data and data feedback to business, and continuously and effectively support the efficient operation of front-end business systems and business intelligence construction with data capabilities. Guiyang Bank is comprehensively planning and implementing in phases to build a data center platform, comprehensively improving data service and data management capability levels, supporting Guiyang Bank's business digital and intelligent development construction.
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With Qujing Bank's rapid growth in business data scale and business development, to further enhance data service and data management capabilities, the company decided to build a data center platform. Through the data center platform, reporting data processing capabilities were improved, ensuring the timeliness and accuracy of reporting; combined with one-stop data development management, reducing data development threshold while improving development efficiency; and improving the company's data governance level.
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AEON is Asia's leading comprehensive retail and service enterprise group, with over 500 member companies. In recent years, as AEON's business continues to develop, data's role in promoting business has become increasingly prominent. The group fully recognizes the importance of data platforms for business development and initiated a data center platform project to establish a unified data platform connecting the group's front and back-end core business systems. Through the data center platform, business sector data is aggregated, data interconnection and standardization are achieved, forming data assets, providing reusable data services and capabilities for business and data development teams based on technology and big data capabilities, creating a data support platform for AEON's digital transformation.
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Through KeenTech's data center platform solutions, Golden Eagle Group connected internal system databases, solved complex report data collection, governance, and visualization issues, unified consumer and product data collection, processing, and analysis applications, comprehensively releasing data value.
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With Taikang Pension's rapid business development, data capabilities in data collection, computing power, benign storage, and full-link management urgently need upgrading to further meet business development needs in batch data exchange, real-time data aggregation calculation, batch data aggregation calculation, data quality control, agility...
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As a key high-tech enterprise in traditional industrial manufacturing. In recent years, with enterprise development and the national "14th Five-Year Plan", in enterprise digital transformation, there are issues such as poor horizontal scalability of existing systems, traditional databases unable to support massive data, unclear boundaries between cloud and edge partitioning, and insufficient edge data storage capacity. Based on these problems and difficulties, there is a need to build an enterprise data center platform, constructing a large-scale data-driven and data-intelligent production service system.
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Through data collection and analysis, SANY fully explores the internal relationships between historical and real-time data of industrial manufacturing enterprises, helping enterprises make efficient and precise digital decisions through data intelligence, aligning with the national "14th Five-Year Plan" and supporting enterprise digital transformation.
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The SAIC MOTOR Group data center platform project, by building unified data system specifications and data standards, establishes unified management caliber unified indicators and standardized models; unifies data from various data sources, breaks data silos, establishes a unified big data center, constructs full-link full-domain data assets, governs data and manages data assets; builds a unified data sharing and exchange center, opening and empowering various systems under data security control mechanisms.
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In the cutting-edge AI big data automotive industry, Nanjing FAW Research Institute empowers intelligent driving, autonomous driving and other cutting-edge technologies through the data center platform's data aggregation, data governance, data development, data application, machine learning, and AI algorithm functional modules; supporting intelligent construction of new energy vehicle systems.
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Through professional big data platforms, the automotive industry has broken through traditional system ceilings, more precisely completing comprehensive digital transformation of production processes and supply chain management, from data collection and storage, business modeling to real-time process monitoring and visual analysis.
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