The First Step in Many MDM Programs
Industry codes, entity identifiers, country codes, units of measure and conversion rates are all examples of reference data. They are relatively static, low volume sets of permissible standard values used to provide context related to events and transactions. Often, reference data is sourced from external sources or industry data providers. Because reference data is shared across an organization and is integrated into both operational and analytical systems, reference data can have a huge impact if it is not managed. Therefore it is critical that your reference data is accurate and consistent. As a result, reference data management is often a critical first step in a full MDM implementation.
Common business drivers for managing reference data include:
- Inconsistent Reporting
- Regulatory Non-Compliance
- Transaction Failure
- Systemic Failure
To be effective, RDM systems must have the right balance of governance in tandem with a robust and flexible business model. Since RDM is usually the first step in building operational master data programs, these capabilities must support a growing implementation.
Key RDM Capabilities & Benefits
Magnitude MDM easily meets the needs of RDM, offering a capability to map data from internal and external sources, managing complex relationships between different reference data representations and data domains across the enterprise, as well as embedded workflow to resolve inconsistencies.
Robust, Multi-Domain Modeling
Magnitude MDM easily supports a wide array of business structures from code lists to complex, multi-path, ragged, self-referencing hierarchies. Our visual modeling capability coupled with a top-down, business-centric approach enables both IT and the business to collaborate in building sensible and effective RDM processes. Reuse makes for a quick, efficient and cost-effective path to adding new domains, objects, attributes, and associations.
Magnitude business information models drive the physical layer through the Magnitude MDM engine and deliver the right amount of automation, governance, and control over the database objects and corresponding load processes.
Magnitude business information models quickly map between reference data sets both within and across domains. Global to local, external to internal, specific to general are quickly defined and implemented with virtually no disruption to existing elements. Changes are automatically captured through Magnitude MDM’s out-of-the-box time variance support.
A robust, customizable MDM workflow provides just the right amount of control over the business process of reference data management. Complete audit history captures what changes were made by whom and at what time. Model-based security controls which users can view, add or update categories or subjects. Data subjects are managed in either working or published context to provide absolute control over which data can be made publicly available.
Any changes to models, subjects, attributes, and associations are captured across time. With this functionality, you can quickly retrieve any subject based on current state or how it existed at any point in time.
Reference data is used to drive key business processes and application logic. Without effective governance, errors in reference data can have a major negative and multiplicative business impact. Reference data management is usually the first step in building an operational master data program. Magnitude MDM can get your organization’s reference data program underway quickly and effectively while setting the stage for a more comprehensive, operational master data program based on the same Magnitude MDM technology.
Other common uses of the Magnitude MDM solution include:
- Hierarchy Management – visually manage and browse multiple different views of data for different uses across systems, easily handling re-organizations.
- Data Harmonization – combine multiple data sources into an integrated, unambiguous entity “golden copy” record that can be used by consuming systems to feed a business process.
- Central Master Data Authoring – create a centralized master data authoring system to create new records, apply custom business rules and then publish to consuming operational systems.