SS-AI Meta SangSangStory

SS-AI Meta

Metadata Management System

A solution to establish, distribute, and manage company-wide data standards management guidelines for the scope of data standardization, data standard uses, data management organization, and key standardization processes.

Minimizing data duplication to
improve efficiency

Continuous monitoring prevents and resolves data inconsistencies between systems to improve corporate efficiency.

Efficiently managing maintenance
and change

Establish, distribute, and manage company-wide data standards for efficiently managing maintenance and change.

Evidence for future improvements
and goal setting

Setting the foundation for future data platforms by establishing data standardization guidelines that are essential for data solution adoption

Project management

  • Project registration and management
  • Users and roles management
  • Standard sets management by project

Target database (DB) management

  • Target DB registration and management
  • Registration and management of managed data types by database management systems (DBMS)

Target DB standardization
analysis

  • Standard data initialization tool
  • Using machine learning for standardization

Standard sets management

  • Registration and management of standard words and domains
  • Creation and management of standard terms
  • Management of standard approvals
  • Change impact analysis
  • Utilizing common preregistered standard sets

DB modeling

  • Modeling with standard terms
  • DB model management and standard analysis
  • Target DB and model gap analysis
  • Reverse engineering
Multi-threading

Project Management

Standardization across projects by sharing standard dictionaries makes it easier to manage multiple projects

Operations Management

The initialization tool makes it easier to initiate operational management for existing configured DBs

DB Management

Standardized terminology for DB modeling and comparison management with actual configured DBs