A five-minute guide to Dataphin
Development
Feature | Demo | Description |
Basic development | Basic development covers data integration, data development, and data administration. It demonstrates the entire process, from importing data and building complex data models or code tasks to managing various tasks. | |
Intelligent development | Intelligent development uses dimensional modeling and automated code generation to improve efficiency. The dimensional modeling framework standardizes business definitions with components such as dimension tables, fact tables, and atomic metrics. After you complete the model design, the system automatically generates executable SQL code. A conceptual model simplifies and abstracts your business, making it easier to understand its core and supporting the creation of data models. Building a conceptual model is a top-down process that moves from a broad view to specific details, covering business units, data domains, and business entities. | |
Intelligent O&M | Artificial intelligence for IT operations (AIOps) effectively addresses the shortcomings of traditional O&M, such as the lack of proactive alerts and precise control over task priorities. You can use baseline and task throttling configurations to monitor and manage baseline instances and effectively throttle task priorities or concurrency. | |
Real-time development | Real-time development improves development and O&M efficiency by productizing real-time engines. The process uses metatables and Flink SQL for low-code development. It also offers features such as visual debugging tools, unified mapping for runtime image tables, isolation between production and development environments, and end-to-end visual monitoring of node status. |
Tag platform
Feature | Demo | Description |
Tag platform |
| Tag Factory builds an end-to-end process from tag creation to service delivery. It offers a one-stop platform for data development teams and engineers to develop and serve tags. This is useful for scenarios such as risk control and marketing. The tag platform lets you develop, manage, explore, and serve offline, real-time, and service tags. It empowers business applications and helps enterprises build their tag assets. This makes tag development efficient, searchable, user-friendly, and manageable. |
Asset governance
Feature | Demo | Description |
Data Standard |
| Data Standard supports business, technology, and management to ensure data consistency, accuracy, and availability throughout its entire lifecycle. This lifecycle includes data collection, storage, processing, and sharing. Mapping rules link data standards to data assets by defining matches between standard properties and asset metadata fields. This process is required to evaluate assets against the standard and ensure that data use complies with specifications. |
Data Quality |
| Data Quality measures how well data meets business needs for accuracy, completeness, consistency, and timeliness. It is a core metric for data reliability and usability. Dataphin provides a complete Data Quality solution with features such as quality monitoring rules, Scheduling Configuration, smart alerts, and quality reports. You can use the governance workbench for closed-loop management of quality issues, including providing feedback, making corrections, and adding items to a whitelist. |
Data security |
| Data security uses technology and management to protect data from leaks, tampering, damage, or loss. This protection covers the entire data lifecycle, from collection and storage to transmission, use, and destruction. Dataphin provides unified capabilities to identify and protect sensitive data throughout its lifecycle. Features such as data classification, identification rules, and security algorithms help you build a complete data security system. This helps ensure data confidentiality, integrity, availability, and compliance. |
Resource governance |
| Resource governance provides statistical analysis of resources. It intelligently identifies low-value data assets and data nodes in the system and suggests optimizations. You can use the governance workbench to ensure efficient resource use, maintain global control over computing and storage costs, and guarantee compliance. This supports stable and sustainable business operations. |
Metadata acquisition |
| Metadata is data that describes other data. It describes the content, structure, source, and relationships of data to help you understand, manage, and use data resources efficiently. Dataphin supports metadata acquisition. It extracts, processes, and centrally manages metadata from different business systems. This supports data governance and improves an organization's ability to organize, retrieve, and analyze data. |
Asset operations
Feature | Demo | Description |
Asset catalog |
| The asset catalog manages metadata from the Metadata Center through unified asset topics. The metadata is then listed in the catalog, either automatically or manually. This helps business users perform asset inventory, data retrieval, search, and consumption. |
Data service
Feature | Demo | Description |
Data service |
| A data service is a technology that encapsulates data into standardized, reusable APIs, interfaces, or applications. Internal and external business users can then invoke them as needed. Manage the full lifecycle of data services, from development and invocation to O&M, to realize the value of your data assets from storage to application. |
Management Center
Demo | Description | |
Row-level permissions |
| Row-level permissions let you control which rows different users can see in the same table. This ensures that roles can only view the data they need. You do not need to create views or split tables. This reduces maintenance costs and effectively secures your data. |
Custom resource groups |
| Dataphin supports managing schedule resources in groups. You can divide resources into resource groups with different quotas. The resource quotas for each group are independent. You can assign specific resource groups to nodes under different projects. This protects resources for core nodes from being preempted and improves resource utilization. |
Cross-tenant publishing |
| Cross-tenant publishing provides one-click migration of nodes, models, and configurations across environments. This makes environment fencing and data governance efficient, secure, and controllable. This feature is useful for migrating nodes between tenants and for isolating development, testing, and production environments in highly regulated industries. |
