What is the approach to managing Atlas metadata?

Atlas Metadata Management uses the following methods:

1. Data extraction and loading: Extracting data from various sources such as databases, file systems, APIs, etc., and loading it into Atlas for management.
2. Data classification and labeling: Atlas organizes and identifies data through classification and labeling, in order to manage and search data more effectively.
3. Data lineage tracking: Atlas can trace the lineage relationship of data, including its origin, transformation, and usage, to help users understand the complete history and usage of the data.
4. Data relationship modeling: Atlas can model and manage relationships between data, such as association relationships between entities, hierarchical relationships, and more.
5. Data quality management: Atlas can evaluate and manage data quality, including monitoring and reporting on indicators such as accuracy, completeness, and consistency.
6. Metadata search and discovery: Atlas offers powerful search and discovery functions, allowing users to quickly find the necessary data and related information through keywords, categories, attributes, and more.
7. Atlas offers detailed security and permission management for metadata, allowing access control to protect the security and privacy of data.
8. Atlas supports metadata governance, including defining data governance rules, managing data governance processes, and ensuring the compliance and trustworthiness of data.

These methods together form the basic framework and functions of Atlas metadata management, helping users better manage and utilize data resources.