AISWare DataOS focuses on the entire process and full life cycle of data integration, processing, governance, security, and sharing, and further provides professional data middle-ground “steward” services to help enterprises drive innovative growth of their business with data and ensure that their business can achieve continuous and high-quality development.
With strong cross-platform unified development capabilities, DataOS can quickly integrate open source software and other third-party software, and perform unified management and operating monitoring on them
The direct access to WebIDE through the Web achieves development at anytime and anywhere, and the container-based service-oriented Web application development ensures the rapid establishment of a consistent development environment
Creating a global SQL-like DSL based on the Flink engine, and unifying the data processing form in and out of the database, so as to achieve a unified data processing experience for unstructured data and non-database data
The service layer provides unified service access, and encapsulates the original subserver to provide external capability support. The logical control layer provides multiple types of control such as hybrid DAG and data flow dependence
Data virtualization access and metadata directory service are coordinated to realize the registration of various heterogeneous external data and help customers access heterogeneous cross-domain target data through traditional tools
When API performs service authorization for different partners and applications, the number of visits, frequency, return data flow, and number of rows can be set to avoid security risks
Combined with forward data management capabilities, the data operation process can be standardized and streamlined. The integrated suite of tools such as integrated component calling, code writing and debugging can be used for data development, with the closed loop covering various data development scenarios
Accumulating capabilities that can be reused by BU based on businesses, and supporting the scenario-oriented opening of data capabilities, tool capabilities, and model capabilities through three types of data domain-oriented standard methods: Data API, Open IDE, and Embedded DSL
Using years of industry understanding to construct a full-data asset management framework system, and standardizing the process from model design to model realization with the design concept of “WYSIWYG” to achieve measurable model management process
Building a data directory for the enterprise panorama based on the standard technical architecture of enterprise metadata management and relying on metadata and graph relationship services, and realizing the provision of “multi-organization, hierarchical, and customized” data dictionary capabilities
Combining the technical application including machine learning to all links in the entire data link to successfully construct a process flow from rule-based manual operation to automatic operation, and supporting the improvement of data quality, data security and job scheduling in strategy management and response processing
Realizing one-stop out-of-the-box deployment through containerized deployment, realizing decoupling of micro-services at the same time, and providing flexible assembly of original sub-capabilities in the data middle-ground
Easy access to achieve “popular utilization”
Reshaping data-based operating and decision-making process
Focusing on data management to enhance value and efficiency
Comprehensively improving data openness and security
The original B-domain and O-domain business models are separately constructed, B and O-domain data are unified and combined with business models for rapid and unified development;a. Rapid integration and exchange of centralized multi-domain datab. Centralized control of business modelc. A variety of model coding modes for all types of developers (lowering the threshold）
1. Through product deployment, it provides complete data asset sorting methods, forms a standardized hierarchical and domain-specific architecture, and lays the foundation for data asset operation.2. It provides drag-and-drop and integrated development and control platform tools, and improves the efficiency of data asset processing.3. It provides a flexible and efficient portal framework, supports rapid assembly and flexible definition of various indicators, and supports rich visualization methods to generate various reports and graphical analysis applications.
Establishment of the standard system: Basic classification standards, data authority planning, meta-model standards, data classification standards, and storage rules. Checkinh the influence of data source through data lineage influence analysis, grasping the data flow, and quickly locating the data problem.