AI Use Cases
synvert Accelerators
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Master data comprises the basic information of a company. It is the core data of business partners such as customers and suppliers, as well as finances, products and locations, and forms the basis for all company processes and functions.
Master data comprises the basic information of a company. It is the core data of business partners such as customers and suppliers, as well as finances, products and locations, and forms the basis for all company processes and functions.
Master data must be distinguished from transaction and inventory data. Position data describes operational quantity and value structures, such as an account balance. The position data is changed by the processing-oriented transaction data, e.g. account inflow or outflow. The transaction data only provides meaningful interpretations when it is assigned to the daster data. Like the trunk of a tree, master data is stable and long-lasting.
Standardization of Master Data elements
Complex Data Integration
Setting up Master Data Governance and Data Stewardship
Use of complex technologies (real-time, mobile, cloud-oriented, etc.)
Coverage of all business processes from the group to the individual companies
We accompany you on this challenging journey right from the start and bring a wealth of experience from many industries for all data domains. Many useful, tried-and-tested utilities help you to set up the MDM system and the necessary organization quickly and efficiently.
synvert supports you in developing a company-wide MDM strategy by working with you to define use cases, plan roadmaps and manage your MDM projects.
We design your MDM platform to integrate seamlessly with your existing systems and test functionality with PoCs and pilots to ensure you can achieve your goals.
With our experience in setting up data governance programs, we ensure that your MDM organization is implemented in a well-thought-out manner. The definition of roles and responsibilities, standards and best practices, as well as workflows for acceptance and review processes, guarantee the long-term success of the program.
In workshops, we work with you to identify relevant data domains and develop models for master and reference data based on our generic industry and data domain models.
At the start of an MDM project, it is important to know what state your data is in. To this end, we analyze your data landscape and determine the quality of your master data in order to then design and implement processes for cleansing, enrichment, golden records, etc. The long-term success of the MDM program is monitored by defining and measuring data quality KPIs.
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