T/MSITISA 03-003.03-2021 Active Group standards

T/MSITISA 03-003.03-2021 Big Data Credit Data Resources Personal Main Data

Publish Date: 2021-11-09 Implement Date: 2021-12-01 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

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Basic Information

Standard Code: T/MSITISA 03-003.03-2021

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: Economic and cultural

ICS Name: Integrated Information Technology (IT)

Publish Date: 2021-11-09

Implement Date: 2021-12-01

Scope

Main technical content: Master data is slow-changing data shared among computer systems. It is a relatively stable and persistent data that defines business objects and ensures the referential integrity of business systems. Master data is selected from metadata, has shared value and is not frequently changed. It is a key and universal data representing business operations. The basic characteristics of master data mainly include: a) It is a shared basic data that can be reused across various business departments within an enterprise, and is in a relatively high-value, highly shared, and relatively stable state. Master data is shared across departments, businesses, technologies, and systems within an enterprise organization, and is the foundation of application system construction, an important analysis object of data analysis systems, and a core data asset of the enterprise; b) Master data is a coding system. Master data is used to describe digital information resources. Master data coding is a summary table describing various master data codes, code names, and code attributes in the construction of master data, and is the basis for master data code query and application. It is also a global and guiding document for master data codes. Completing the standardized construction of personal information master data in big data credit investigation is the cornerstone of personal information master data management. Good personal information master data construction can help build a complete big data credit investigation data governance system. To construct personal information master data in big data credit investigation, we should classify and code master data, define master data structures, and consider factors such as master data sources, data management levels, data dimensions, the generation process and application value of personal data in related credit business environments, and the constraints between data. Personal information master data management in big data cr