The Big Data Operating System (BD-OS) is supported by PERCENT's big data full-stack technology capability, provides data access, governance, processing, management and service capabilities, realizes one-stop data lifecycle management, and makes data be "input, managed, governed, seen, controlled and shared", helping customers manage data assets at a low cost in an efficient way and exerting data efficiency.
It is compatible with a variety of domestic software and hardware, covering chips, complete machines, operating systems, middlewares, databases and applications, and is widely compatible with Xinchuang Ecology.
The whole process is visible, the operation is simple and fast, and the use threshold is low. It supports the functions of intelligent data exploration, intelligent recommendation, batch operation, import and export, and can switch freely in different environments and greatly improve the efficiency of data development and governance.
It adapts to various underlying storage computing platforms, including HDP, CDH, Huawei FI and MPP databases Guass200, Greenplum, etc.; supports containerized deployment, and easily completes the deployment of complete product in half an hour based on a zero basis.
All core components are of high availability, and can operate stably for 7*24 hours, with the stability reaching up to 99.99%. During the practice of hundreds of projects, we continuously refine the high stability of products.
It is compatible with a variety of domestic software and hardware, covering chips, complete machines, operating systems, middlewares, databases and applications, and is widely compatible with Xinchuang Ecology.
The whole process is visible, the operation is simple and fast, and the use threshold is low. It supports the functions of intelligent data exploration, intelligent recommendation, batch operation, import and export, and can switch freely in different environments and greatly improve the efficiency of data development and governance.
It adapts to various underlying storage computing platforms, including HDP, CDH, Huawei FI and MPP databases Guass200, Greenplum, etc.; supports containerized deployment, and easily completes the deployment of complete product in half an hour based on a zero basis.
All core components are of high availability, and can operate stably for 7*24 hours, with the stability reaching up to 99.99%. During the practice of hundreds of projects, we continuously refine the high stability of products.
It is compatible with a variety of domestic software and hardware, covering chips, complete machines, operating systems, middlewares, databases and applications, and is widely compatible with Xinchuang Ecology.
The whole process is visible, the operation is simple and fast, and the use threshold is low. It supports the functions of intelligent data exploration, intelligent recommendation, batch operation, import and export, and can switch freely in different environments and greatly improve the efficiency of data development and governance.
It adapts to various underlying storage computing platforms, including HDP, CDH, Huawei FI and MPP databases Guass200, Greenplum, etc.; supports containerized deployment, and easily completes the deployment of complete product in half an hour based on a zero basis.
All core components are of high availability, and can operate stably for 7*24 hours, with the stability reaching up to 99.99%. During the practice of hundreds of projects, we continuously refine the high stability of products.
The privacy, compliance, auditability and traceability of data can be guaranteed through security technological means such as tenant isolation, fine-grained data authority and data encryption, which can protect the data sharing and application of the enterprise.
It clearly describes the data assets through functions such as data asset directory, asset retrieval, and asset traceability, links business metadata and technical metadata, connects data developers and data users, and helps data administrators easily manage and operate data assets, so as to realize visible, searchable, usable and operable data.
For different data processing scenarios and different data processing groups, it provides script development and drag-and-drop design and development tools to realize the rapid fusion processing of offline data and real-time data, thus greatly improving data development efficiency and reducing development costs.
It provides a visual, hierarchical and subjective data modeling method, and builds a data model based on data standards and data warehouse standards, which can clearly present the data relationships, accurately express business logic, and organize and design data in a convenient and quick manner.
It provides data standard management, metadata management, lifecycle management and data quality management, builds an integrated data governance system, defines data quality rules from multiple perspectives, comprehensively monitors all links of data lifecycle, realizes comprehensive audit and early warning, and makes data governance well-founded through a strict data quality scoring mechanism.
It provides intelligent data exploration tools to help the data implementers find out the data background and define the data access scope and method in a more accurate and quick manner; supports full visual access to multi-source heterogeneous data, and supports 20+ data sources, including structured and unstructured data, and supports full and incremental access to offline and real-time data.
The privacy, compliance, auditability and traceability of data can be guaranteed through security technological means such as tenant isolation, fine-grained data authority and data encryption, which can protect the data sharing and application of the enterprise.
It clearly describes the data assets through functions such as data asset directory, asset retrieval, and asset traceability, links business metadata and technical metadata, connects data developers and data users, and helps data administrators easily manage and operate data assets, so as to realize visible, searchable, usable and operable data.
For different data processing scenarios and different data processing groups, it provides script development and drag-and-drop design and development tools to realize the rapid fusion processing of offline data and real-time data, thus greatly improving data development efficiency and reducing development costs.
It provides a visual, hierarchical and subjective data modeling method, and builds a data model based on data standards and data warehouse standards, which can clearly present the data relationships, accurately express business logic, and organize and design data in a convenient and quick manner.
It provides data standard management, metadata management, lifecycle management and data quality management, builds an integrated data governance system, defines data quality rules from multiple perspectives, comprehensively monitors all links of data lifecycle, realizes comprehensive audit and early warning, and makes data governance well-founded through a strict data quality scoring mechanism.
It provides intelligent data exploration tools to help the data implementers find out the data background and define the data access scope and method in a more accurate and quick manner; supports full visual access to multi-source heterogeneous data, and supports 20+ data sources, including structured and unstructured data, and supports full and incremental access to offline and real-time data.
The privacy, compliance, auditability and traceability of data can be guaranteed through security technological means such as tenant isolation, fine-grained data authority and data encryption, which can protect the data sharing and application of the enterprise.
It clearly describes the data assets through functions such as data asset directory, asset retrieval, and asset traceability, links business metadata and technical metadata, connects data developers and data users, and helps data administrators easily manage and operate data assets, so as to realize visible, searchable, usable and operable data.
For different data processing scenarios and different data processing groups, it provides script development and drag-and-drop design and development tools to realize the rapid fusion processing of offline data and real-time data, thus greatly improving data development efficiency and reducing development costs.
It provides a visual, hierarchical and subjective data modeling method, and builds a data model based on data standards and data warehouse standards, which can clearly present the data relationships, accurately express business logic, and organize and design data in a convenient and quick manner.
It provides data standard management, metadata management, lifecycle management and data quality management, builds an integrated data governance system, defines data quality rules from multiple perspectives, comprehensively monitors all links of data lifecycle, realizes comprehensive audit and early warning, and makes data governance well-founded through a strict data quality scoring mechanism.
It provides intelligent data exploration tools to help the data implementers find out the data background and define the data access scope and method in a more accurate and quick manner; supports full visual access to multi-source heterogeneous data, and supports 20+ data sources, including structured and unstructured data, and supports full and incremental access to offline and real-time data.
For newspaper offices, publishing houses and other media industries, it provides unified data resource aggregation capability, aggregating Internet data, manuscript data, behavior data, etc., to form standard data areas after data governance and data processing, after that, by using the tools such as text analysis, intelligent retrieval and intelligent recommendation provided by the big data platform, it assists users in intelligent collecting and editing, and improves the collecting and editing efficiency.
For retail, manufacturing, e-commerce and other industries, it establishes unified data standards, integrates business data of all links, and realizes enterprise data capitalization. It is really user-oriented, by using the data analysis mining technical capacities provided by the big data platform, it deeply analyzes user behaviors, establishes a full customer group operation system, and drives marketing and operation with data.
It helps governments at all levels gather various government data, compile unified government data standards and specifications, form subject data after data governance and data processing, and present the directory of government information resources by subject. It fully mines the innovation support potential of data resources, provides data support for the construction of government affairs information application system, and improves the service level of government affairs fine management.
For newspaper offices, publishing houses and other media industries, it provides unified data resource aggregation capability, aggregating Internet data, manuscript data, behavior data, etc., to form standard data areas after data governance and data processing, after that, by using the tools such as text analysis, intelligent retrieval and intelligent recommendation provided by the big data platform, it assists users in intelligent collecting and editing, and improves the collecting and editing efficiency.
For retail, manufacturing, e-commerce and other industries, it establishes unified data standards, integrates business data of all links, and realizes enterprise data capitalization. It is really user-oriented, by using the data analysis mining technical capacities provided by the big data platform, it deeply analyzes user behaviors, establishes a full customer group operation system, and drives marketing and operation with data.
It helps governments at all levels gather various government data, compile unified government data standards and specifications, form subject data after data governance and data processing, and present the directory of government information resources by subject. It fully mines the innovation support potential of data resources, provides data support for the construction of government affairs information application system, and improves the service level of government affairs fine management.
Inquiry