Building data assets to enhance corporate value by building a clear data architecture and management system

Data governance maintains the data architecture consistently, provides a consistent expression method for elements with abstract contents, guides and manages to build company-wide data assets and interoperate with changes, and defines the components of the system
The goal of data governance is to secure the data for company's vision and goals, and provide timely data to users in desired form on a stable service by implementing an environment that can provide reliable, accurate, safe, and accessible data to meet the company's business requirements.

The systematic way to build corporate data governance

• 01

  Provides an integrated perspective of standards and methods based on a data architecture framework consisting of strategies, policies, processes, content, organizations and underlying systems

• 02

  The guidance area provides detailed criteria and measures for organization, roles, responsibilities, data standards, structure and quality for data management.

• 03

  The process area provides data standards, models, procedures for quality management, detailed criteria and measures for roles, responsibilities, and more.

• 04

  The content area manages data models, data quality, and data standards from a classification system that logically classifies data sets.

• 05

  Conduct the activities that improve the technology, process, ability to perform guidance as well as ensure the data quality and accuracy for efficient management and supply data required by the business.

• 06

  The base system is important to support organizations, roles, responsibilities, and processes, and includes related rules to validate and control standards defined in data standards, data models, and data quality.

Methodology for systematic data governance management