Metadata Center extracts, processes, centrally stores, and manages metadata from various business systems to support data governance and enhance the organization, retrieval, and analysis capabilities of internal organizational data.
Prerequisites
Metadata acquisition for relational databases is supported by default. To collect metadata from other data source types, you need to purchase the corresponding features.
For versions earlier than v5.3, you must initialize the Metadata Center in the metadata warehouse tenant before collecting metadata from certain data sources. These data sources include AnalyticDB for MySQL 3.0, PolarDB-X (formerly DRDS), SAP HANA, and Hologres. For v5.3 and later, you can configure acquisition tasks directly without this initialization.
Metadata Center initialization configuration can only be performed when the engine of the metadata warehouse tenant is MaxCompute, Hadoop, or Transwarp TDH 9.3.x.
Permission description
Only super administrators, system administrators, and global custom roles with metadata feature viewing permissions can view metadata-related menus.
Metadata introduction
Metadata is information that describes the characteristics of data. It provides detailed descriptions of data content, source, format, and structure, often referred to as "data about data." The purpose of metadata is to make data easier to understand, manage, and use. It helps users identify and locate specific datasets and supports data organization and retrieval. Additionally, metadata promotes data consistency and interchangeability, providing a foundation for data governance compliance and data quality management. Through metadata, organizations can effectively monitor and analyze their data assets to achieve better decision support and business insights.
Metadata classification
Metadata is classified according to its purpose into Technical Metadata, Business Metadata, and Management Metadata.
Technical metadata stores data about the technical details of data warehouse systems and is used for developing and managing data warehouses. In Dataphin, technical metadata is displayed as technical assets, showing information such as data domains, subject areas, projects, storage classes, storage formats, and lifecycles.
Business metadata describes the data in the data warehouse from a business perspective. It provides a semantic layer between users and the actual system, enabling business personnel without computer technology knowledge to understand the data in the data warehouse.
Management metadata involves organizing, integrating, and managing the technical and business metadata using scientific and effective mechanisms. It provides metadata services to relevant business, development, and other users to meet different business scenario requirements and supports the development and maintenance processes of enterprise business systems and data analysis.
Metadata entry
In the top menu bar of the Dataphin homepage, select Administration > Metadata.
On the Metadata page, the left navigation pane displays the entry points for various features.
Level-1 menu
Level-2 menu
Description
Metadata acquisition
Collection overview
Metadata supports a variety of collection source types, such as traditional databases like MySQL and Oracle, and big data storage like Hive, Hologres, etc. You can view created collection tasks, created data sources, collection object types, and supported versions for different data source types.
Collection tasks
Connect to the specified data source through collection adapters to collect object metadata information from the source database into Dataphin. The collected metadata is parsed by built-in resolvers, stored, and presented in a unified manner.
Collection instances
These are instance tasks generated by collection tasks based on timed scheduling or manual task execution.
Metadata management
Business system metadata
Displays the collected metadata information in list form, allowing you to query data from different perspectives.
General configuration
Business systems
Configure the business system to which metadata collected from specified sources belongs. This can be used for object filtering in asset checklists and directories, business system lineage relationship display, and other scenarios.
Data detection
Configure the range of data tables that can be automatically detected, control the retention period of data detection records, the maximum number of detection tasks that can run simultaneously globally, the execution timeout for detection tasks, and set parameters to use resources more efficiently.