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Gone are the days when doing business meant doing so only within the borders of the organization. What used to be single-source data is now multi-source. Today’s business world is comprised not only of disparate systems and groups, but users as well; open networks with business partners, customers and suppliers; and diverse architectures and business functions, not to mention global outsourcing and off-shoring efforts. The net? Every link is an exposure and every data element is a risk. In short, business today means your network is the enterprise.
Like any dynamic entity, your organization—along with its data—changes daily. And as the data (whether structured or unstructured), is aggregated and consolidated, to successfully leverage the data across the organization, it must be treated as an enterprise asset. This is especially important for master data, the key business facts used across multiple business applications.
Yet, for many organizations with data-sharing environments, complex silos and isolated stovepipes of information and systems hinder business responsiveness and decision makers’ ability to make informed decisions. Collaboration among users, functions and systems is often fraught with few clear-cut roles and responsibilities for protecting or enhancing data. Challenges like these illustrate why data governance has emerged as a strategic priority for organizations of all sizes.
This white paper will describe how engaging in a master data management (MDM) project enables effective governance of data—specifically master data—and achieves maturity in key categories of the IBM Data Governance Maturity Model.
Data governance and Master Data Management: A symbiotic relationship
In a world where data fuels the business, IT (the data custodian) has to deliver the data effectively and accurately to the entire business. For it to remain viable and relevant, there must be organization-wide support for transforming data, specifically master data into information.
For most organizations, this critical business information is replicated and fragmented across business units, geographic branches and applications. Enterprises now recognize that these symptoms indicate a lack of effective and complete management of master data. IT departments have attempted to gain control over this master data using a variety of methods. But few have demonstrated true success due to their reliance on existing, but repurposed, systems and applications.
What is master data management?
Master Data Management (MDM) is application infrastructure (not a data warehouse, enterprise application, data integration or middleware), designed to manage master data and provide it to applications via business services. MDM enables users to deliver a new class of information-rich applications based on business processes and accurate and complete master data. It supports, augments and leverages your investment in existing applications.
MDM offers:
- An approach that decouples master information from individual applications and unifies it.
- A central, application- and process-neutral resource.
- Ensures consistent, up-to-date master information across business processes, transactional and analytical systems.
- Proactively addresses key data issues such as governance, quality and consistency.
- Simplifies ongoing integration tasks and new application development.
A master data solution that manages master data domains (the high-value, business-critical information about customers, suppliers, products and accounts) and offers IT the capability to transform information into corporate knowledge is a good place to begin getting control over disorderly data.
In general, master data management solutions should:
- Consolidate data locked within the native systems and applications.
- Manage common data and common data processes independently with functionality for use in business processes.
- Trigger business processes that originate from data change.
- Provide a single understanding of the domain—customer, product, account, location—for the enterprise.
MDM products vary in their domain coverage, ranging from specializing in a single domain such as customer or product, to spanning multiple and integrated domains. Those that span multiple domains help to harness not only the value of the domain, but also the value between domains, also known as relationships. Relationships may include customers to their locations, to their accounts or to products they have purchased. This combination of multiple domains (customer, product, account, location, etc.), multiple functions (operational, collaborative authoring, and analytical) and the full set of capabilities in a transactional environment is known as multiform master data management.
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