快乐飞艇

Inspection and Testing Information Management: 400-686-4199 Data Asset Management: 400-643-4668 Supply Chain Management: 400-629-4066
Product description

In the process of enterprise data standardization, it is expected to feedback value to business through data standardization management. So, the importance of data quality can not be overemphasized. In this process, the generation of low quality data is inevitable, because the mass data initialization, unprocessed historical data diffusion and emergency businesses will all affect the quality  of data standard coding library. Thus, what the enterprises can do is to control the probability of generating low quality data and to discover low quality data in time and deal with it effectively. Therefore, the correct understanding on enterprise data quality management is that it is to reduce and control the production rate and the existence rate of low quality data through scientific, effective and professional management and technical supports, and discover low quality data in time and deal with it effectively, and keep standard code library's high health degree rather than not generating low quality data.

Product Functional Framework

Data quality management platform (DQMP) is the core standard component of SunwayWorld's information standardization and management integration Platform solution (6P+2E+Mobile), ensuring the data quality of the enterprise data standard library and transparent visual analysis of the standard data code library. However, due to factors such as the large amount of data, the complexity of data information and the high professional requirements of the data coding library, manual guarantee of quality is difficult. Thus, the standard data coding library should be tested by professional quality management tools so as to discover incomplete and abnormal (but real) data to be processed, iterant and noise data to be removed. Data health analysis should be provided by a professional data quality management platform in order to steering data cleaning and governance, so as to ensure the uniqueness, integrity,consistency, and improve data quality.

Features

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Data quality control and configuration

Through the Data Quality Management Platform, data models of different types are configured with the corresponding quality control and analysis parameters to achieve normal quality monitoring and management on standard data of different types, thus realizing accurate duplicate checking and fuzzy duplicate checking among data and providing configurable data verification functions. The platform also supports verification and inspection of data uniqueness, completeness and consistency. 
It supports the configuration of similar data matching conditions. 
The system supports regular repeated code inspection on master data and provides the list of repeated codes of master data.
Support accurate duplicate checking function and configure duplicate checking rules.
Support batch export of the list of repeated codes of master data.
Support to establish unified approval process.
Support publication of the list of repeated codes and collection of opinions: the list of repeated codes of master data will be only announced to subsidiaries or business units which use to-be-deleted master data in the business system.
Achieve various inspection functions on data through configurable data inspection conditions. 
processing conditions of each business system of the released list of repeated codes: establish the mapping relation of repeated codes of master data and track the business processing conditions of deleted master data (including the processing status of outstanding business and master data).
Support approval, publication, opinion collection, release and export of the list of repeated codes; realize the establishment of data constraint rules.
Realize mandatory inspection function on fields.
Realize inspection function on relationship fields.
The system supports regular health analysis of master data and provides health analysis reports of master data.