Inspur data cloud products

It has formulated a unified standard and specification for water network information technology in the province, integrated and promoted the smart application of water-related business, built an information platform for the interconnection and sharing of major water-related information in the province, and realized the smart management of “a set of standards, a sensing network, a big data center, a map, a platform, and a window”.

It has built an integrated big data center platform supported by the cloud, formed an information resource service mechanism of “one-time collection, multiple use, one-stop collection, and multi-party use”, and built a smart governance model of dynamic real-time sensing, collaborative linkage of urban governance, and intelligent handling of emergencies.

By providing data services and application capabilities, it realizes the “upper and lower integration” of data such as people/places/events/things/situations/organizations, solves the problems of duplicate data collection and data islands at the grassroots level, optimizes urban management methods, empowers urban governance with digitalization, reduces the burden and increases efficiency for the grassroots, and provides data support for urban development decision-making.

Through the summary, deduplication, and cleaning of the basic population data of each department, a list of basic personnel is formed, and the list of basic personnel is sent to the public security bureau for verification, and the public security bureau verifies whether the names and ID numbers of the personnel exist in the data of the public security bureau, and feeds back the verification results to the relevant data management bureau.

Jinan Big Data Bureau innovatively proposed the public data governance cloud service model to provide “a la carte” services for relevant government departments, and each department can apply for data governance services to the Jinan Big Data Platform according to the needs and catalog lists, realizing the transformation of the data governance model from simple technical operation and maintenance to efficient comprehensive “cloud services”.

The penetrating application of Urumqi legal person equity mainly gathers the basic information of individuals, legal persons, social organizations, public institutions and other units such as the Market Supervision and Administration Bureau, the Civil Affairs Bureau, and the State Commission Office of Public Sectors Reform to form the basic object of legal person equity through multi-data fusion. After standardized data modeling, cleaning and governance, and standardization, a comprehensive data perspective is constructed from the establishment of legal person enterprises, investment, membership, tax payment, law-related and litigation-related data across the whole city, so as to provide effective support for the regulation of relevant law enforcement departments.

The platform helps Henan provincial tax big data to realize high-speed processing and BI analysis of massive data such as core collection and management, individual income tax, and invoice system, with the following data volumes: 2-3T incremental logs per day, 0.2-1 billion large tables, 5000-6000 tables, and 2000-3000 code tables.

It helped CMHK, the Hong Kong branch of an operator, to provide enterprise-level multi-tenant capabilities to store and process global data in the B-domain, O-domain, and M-domain, and support the operation of multi-domain core services. With 100,000+ daily running tasks and 2PB of stock data, it provides enterprise data asset management and data sharing capabilities.

Before the government affairs center of a provincial capital opens government affairs data to financial enterprises, first desensitize through IDPS to develop an enterprise credit scoring system. 

Develop models such as credit reporting and financial quick loans to ensure data security control, meet the needs of financial customers, and promote secure data sharing.

For a bank customizing credit products, it is necessary to grasp the credit model of the municipal enterprises. Multi-department data is used to analyze the total number and distribution of enterprises. Through the debugging of IDPS, financial enterprises can test the data dimension, optimize the algorithm, and form an exploration report.