The direct value that data standardization brings to business is that high quality and high credible data acting on business process and system interaction, which will finally realize decision analysis support. As a combination of technology and theory, the standardization management of data requires the elaboration and decomposition of data’s complete life-cycle into application, submission, review, release, maintenance and archiving and the professional and standardized management of data of assorted stages. To provide quality data for enterprises through data life-cycle management stands out in enterprise data standardization management.
Data life-cycle management platform (DLMP) , providing high quality and reliable data for business, is the core standard component of SunwayWorld's information standardization management integration platform (6P+2E+Mobile), which realizes the comprehensive management of data life-cycle and provides functions catering for every requirements of data management from technology to business such as data standard template application, complete and accurate intelligent verification and similarity detection, smart reminder of data audit, flexible audit process configuration, flexible data composition element privilege configuration, intelligent data release, easy data maintenance modification, convenient data filing, data version control according to various kinds of data standardization execution specifications generated in line with the data standardization management platform configuration.
Data application verification
Master data can be applied online during which process there is automatic verification in line with pre-defined data constraint rules side by side. Data application template constraints, ancillary filling support, data characteristic permission configuration and similar master data for users' reference as well as instant message reminder function are provided.
The system provides a background task queue function, which allows a large quantity of data import tasks executing background, solving the waiting problems of users during the traditional data import process.
Master data verification makes accurate duplicate checking and fuzzy duplicate checking among data, supports similarity detection and thesaurus detection and also provides configurable multiple data verification functions. It also supports uploading of attachments of various formats.
Data verification management
Realize online approval of master data, template, value library, alias library and other workflows, make automatic data verification based on the defined data constraint rules in the approval process, provide similar master data for experts' reference and record their approval opinions.
Support user-defined approval process, provide graphical workflow engine and realize version control.
Make data permission control in processes of data application, approval, maintenance, release and other processes; maintain, check and make other function restrictions on meta property constituted even by the minimum data; support enterprises' detailed management on data permission.
Data maintenance management
Realize online maintenance of master data coding and attribute information, rule template and other information (including add, modify, delete and outage) and increase, delete, modify and check master data, and also realize other functions. The system can make version management on change of master data and automatically establish history logs of data change. The system can make effective management on the status of various master data, including application, approval, release and other process status. In case of any modification of master data in the application process, the system will automatically provide an e-mail and SMS to notify personnel in charge of master data management. In addition, it can examine and approve the workflow of the maintenance contents and after approval, the updated contents will come into force.
Data queue scheduling
The data lifecycle management process should take business scenarios of massive data process and multi-task concurrence into account and provide system support for such business scenarios by making use of the smart data queue scheduling function.