By David Butler
1. Profile. For each master data business entity to be managed in a central master data repository, all existing systems that create or update the data must be assessed for data quality. This includes evaluating the completeness of the data and the distribution of values, and determining the acceptable range of values. Once implemented, the master data management (MDM) solution will provide the ongoing data quality assurance. But starting out with a thorough understanding of data quality in each contributing source will help you go forward with the highest-quality data in the subsequent steps of the MDM implementation. Oracle Enterprise Data Quality products provide this key first-step capability.
2. Consolidate. Consolidation is the key to managing master data. Without consolidating all the master data attributes, such steps as creating blended records from multiple sources are not possible. This is the fundamental prerequisite to operational master data management. Even the thinnest registry-style hubs must consolidate enough data to ensure that federated data is located and duplicate data is identified. Every Oracle MDM hub product provides a data model and import workbench for source system management.
3. Cleanse. Once master data is consolidated, it can be cleansed and governed. Now is the time to consider how specific business objects will determine which data quality tools you require. Managing unstructured item data is very different from managing structured party data. Items need semantic-based technologies, while party data needs pattern matching. Or, a combination of these two can standardize, deduplicate, and augment master data across the board. Oracle Enterprise Data Quality products are fully integrated with Oracle MDM hub products to provide this capability.
4. Govern. A sound data governance strategy not only aligns business and IT to address data issues but also defines data ownership and policies, data quality processes, decision rights, and escalation procedures. It’s smart to settle these issues early in the process, because the biggest obstacles to MDM usually have more to do with corporate culture, resistance to change, and jurisdiction issues than with technological challenges. To overcome these obstacles, you need organization, processes, and tools for establishing and exercising decision rights regarding data management. Data governance is essential to ensuring that data is accurate, appropriately shared, and protected. Every Oracle MDM hub product provides data governance capabilities for the business user.
5. Share. Clean, augmented, quality master data provides few advantages to your organization if it resides in its own silo. For MDM to be most effective, a modern service-oriented architecture (SOA) layer is needed to propagate the master data to the applications that can best make use of it. SOA and MDM need each other if the full potential of their respective capabilities is to be realized. Oracle MDM products and Oracle SOA Suite are fully integrated to maximize the business value of each.
6. Leverage. MDM creates a single version of the truth for every master data entity. This data feeds all operational and analytical systems across the enterprise. But more than this, key insights can be gleaned from the master data store itself. A 360-degree view is now available for all business processes. Alternate hierarchies and what-if analyses can be performed directly on the master data.
The six steps above define the capabilities that any MDM solution must execute fully. Partial, nonintegrated solutions abound, but total coverage for all master business entities combined with a full set of built-in MDM business processes brings the full value of MDM to your enterprise. This is exactly what the Oracle MDM solution does.
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