As a big data development and governance platform, WeData boasts the following advantages:
Based on open-source
WeData supports open-source access and widely supports common big data open-source technologies, such as Hadoop, Hive, Spark, etc. Users with experience in open-source software can easily transfer their experience.
Ease of Use
Through the abstraction of core concepts such as workspaces, data sources, and workflows, and their organic integration in modules like data maps and data quality, users can quickly understand and seamlessly use WeData for data development and governance.
Cost reduction and efficiency improvement
WeData provides many features to help users reduce costs and improve efficiency, such as the data temperature feature in the data map, which assists in identifying infrequently used but high-cost data for cleaning or transferring; the canvas feature in workflow development enables easy organization of workflow task dependencies through drag-and-drop.
High Security and Stability
The data security module provides data access control capabilities, enabling pre-approval, interception during the process, and post-event audit for data access rights; data content control capabilities allow for business data desensitization, establishing the last line of defense for data security.
Robust and powerful high availability, CLB, and timely, multi-channel monitoring and alerts also ensure the stability of service status and task execution.
Rapid realization of big data monetization
The product helps users quickly discover and understand data through integrated operations, solves complex data pipeline development with DataOps, liberates data development productivity, and achieves rapid data R&D and delivery.
Meeting business self-service needs
Data analysts/business personnel can focus more on the business logic itself, combined with the product's self-service data discovery, exploration, and analysis capabilities, to meet the smoother data usage needs of different roles.
Reducing corporate management costs
Data development requires cross-team and multi-role collaboration, but traditional data tool architectures are fragmented and difficult to coordinate. The product provides a tool basis for different roles to perform their duties and collaborate effectively through spatial division.
Enhancing enterprise data quality and trustworthiness
The product resolves the issue of "double-skinning" of data through pipeline operations in development, testing, and production spaces, ensuring data compliance, standardization, quality monitoring, and improvement throughout, securing data quality.