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Industry SolutionsEnterprise Data Middle Platform Project for a Group Company
Today, with the rapid development of big data, AI and cloud computing technologies, data has become an important asset of the company. How to fully explore the value of data, support business development, and support the business innovation of the company's information services and data products poses a new challenge to the company's overall data architecture. The overall construction goal of the project is to meet regulatory requirements; manage enterprise-level data standards; strengthen data quality control traceability; sort out data relationship veins; inventory the group's data assets and form an asset list, etc.
Standardizing models is difficult, frequent changes complicate model management, restoring models from metadata is challenging, and the platform must support real-time collaborative design.
Provide a unified data model management platform and apply unified modelling tools in a web access mode. Open application services for each legal entity in a tenant mode, and achieve the business management goal of unified modelling tools and business individuality by means of role and authority control.
Planning model catalogue system, including model technology management system and business subject classification system, realizes model tracking and classification from both technical and business dimensions, and meets the application of model information by personnel in different roles. At the same time, through the model authorization mode, it achieves the control of permissions (invisible, read-only, editing) for model management and data structure security control.
New business model design is completed in different ways, such as importing Excel templates, accessing the data structure resources of the metadata platform, and quickly referencing the model structure in the model library. The model design relies on different types of existing data dictionaries, such as resource reuse and other modes, to meet the needs of multi-form model design, and at the same time, it provides a graphical ‘drag-and-drop’ modelling method. At the same time, it provides graphical ‘drag-and-drop’ modelling to achieve intuitive and easy-to-use effects.
In order to meet the combination of storage and model design for localized adaptation, flexible database adaptation mode is provided to quickly adapt the database syntax and improve the response speed of on-site adaptation.
Combining the tenant management mode in a Web way, it achieves the goal of a common set of modelling tools, unified authorization, unified operation and maintenance, and unified data security control for different legal entities within the group. Different model design modes of each tenant are solved in different model design modes to meet the personalized model design requirements of different user groups; different sub-platforms such as data standard management, metadata management, and data development are coordinated in the data middle-platform, so as to realize the management mode of modeling according to standards, one-key reuse of metadata resources, modeling according to needs, development according to needs, and seamless coordination of modeling and development, improve development efficiency, reduce data governance and input, and strengthen the construction requirements for the whole process control of data development. It also improves development efficiency, reduces data governance, and strengthens the construction requirements for the control of the whole process of data development.
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ORIGIEN Data Asset Platform
The ORIGIEN Data Asset Platform integrates data governance, data middle platform, and data tools into a single data intelligence foundation to enhance data governance and unlock the value of data assets.
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Big Data Platform/Data Lake
Enables integrated collection, management and consumption of middle platform source data, automating raw data ingestion and governance
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Data Middle Platform
Enables high-level data integration and capability reuse through four key dimensions: platform consolidation, data governance, service development, and scenario activation to achieve data-as-a-service.
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