Dataphin:Upgrade configuration - Semi-managed

Value-added feature package

Description

Real-time R&D

Processes stream data based on real-time engines. Supported engines include Alibaba Cloud Real-Time Computing Flink, Apache Flink, and FusionInsight Flink.

Artificial intelligence for IT operations

Ensures the timeliness of business data output and system stability. It also reduces manual O&M costs and improves O&M efficiency. It includes baseline monitoring and throttling configuration features.

Data Standard

Provides unified creation and management of standards, reference data management, and association of standards with asset metadata. Combined with quality monitoring, it helps enterprises enhance end-to-end asset governance across all stages.

Asset Quality

Supports quality monitoring of data assets from physical and logical perspectives. It helps you efficiently configure quality rules and run verification jobs. It also provides data quality reports and overviews with clear permissions to help you quickly understand rule coverage and identify data quality threats.

Asset Security

Manages data assets from a security perspective by setting data classification and grading, configuring identification rules, and setting up desensitization policies. It helps you get a full picture of asset security, identify security risks, and assist in formulating and implementing data security control policies.

Resource Administration

Establishes a closed loop driven by metadata acquisition, unified metadata model creation, and core governance items. This supports the application layer capabilities of data asset management, serves asset managers and developers, and builds a manageable and controllable data asset health system.

Data Service

Data Service unifies data subject units through standardized and configuration-based methods. It supports self-service API configuration, testing, pre-release, publishing, and call monitoring for subjects. It provides field-level control over data usage permissions, which lowers the barrier for business data consumption while ensuring the security of data development.

OpenAPI

OpenAPI is the external operational entry point provided by Dataphin. It lets developers share data, features, and services among different applications, helping them develop and extend applications more efficiently. Dataphin provides OpenAPI interfaces for multiple functional modules, including development, O&M, assets, and platform management.

Real-time integration

Supports incremental integration from MySQL, Oracle, and PostgreSQL to Hive, Kafka, DataHub, and MaxCompute. It also supports synchronization from Microsoft SQL Server and IBM DB2 to Kafka.

Tag Factory

Provides offline and real-time tag development features for tag builders, such as developers or business personnel with development capabilities, through a visual tag processing method. This improves the efficiency of tag development and lowers the development barrier.

Registered Scheduling Cluster

Supports connecting to a database in another network through a registered scheduling cluster. This avoids data transmission across networks.

Tenant Quantity

Supports creating multiple tenants in a single Dataphin instance. Different tenants can rely on different compute engines.

Row-level permissions

Supports row-level permission control for tables in compute sources and data sources.

Asset Operation

Includes folder management (folder planning, asset listing), asset consumption, and asset folder features.

• Folder planning: Organizes assets by subject and configures their visibility. This achieves unified management of all assets to simplify asset search and consumption.

• Asset listing: Supports manual and automatic listing. During the listing process, you can complete asset property information and control asset visibility permissions.

• Asset folder and consumption: View the asset list, use various search methods, and view asset details.

Metadata Center (Data Management + metadata acquisition)

Supports extracting, processing, centrally storing, and managing metadata from various business systems to support data governance. It also enhances the organization's ability to organize, retrieve, and analyze internal data.