There’s a very interesting relationship between master data management (MDM), service oriented architecture (SOA) and business process management (BPM). Read more
For more information on Joan, please see her LinkedIn profile — Dan Power
Let’s not allow Master Data Management (MDM) to become just another silo of data! MDM and Service-Oriented Architecture (SOA) together, create a strong partnership in your enterprise architecture.
1. Data Quality = Add Quality to SOA
SOA enables business functionality as a service. However, it does not guarantee quality of the data on which it’s operating. That’s a serious gap, which is filled by including MDM in a service-oriented architecture. True business value is realized as services start leveraging the high quality data in the MDM hub and the services which surround it.
2. Data Management Services Offered by the MDM Hub
MDM abstracts the governance of data by consolidating it into a central data model; conducting all data cleansing, augmentation, cleansing, and standardization; and creating a ‘gold standard’ source. These data management functions are centralized in the data hub and are hidden from the consumers of the cleansed data. Maximize the value of these services by consuming them from other applications that need to perform data quality processing external to the data hub.
3. Data Offered by the MDM Hub
Data services allow the consuming application to access and manipulate hub data from a service layer as a supported data source. Layering data services on the MDM hub hides the implementation of federated queries that gather the data requested by the consumer.
4. SOA, MDM, and middleware
SOA, integration middleware (Enterprise Service Bus or ESB), and MDM together can manage the detection of data changes in the source applications and propagate them from the source applications to the MDM – or from the MDM back to the consumers. With the addition of Business Process Execution Language (BPEL) and a business rules engine, a data change detected in a source can be captured, cause the data quality business rules to be executed on the data, and place the data back on the ESB to be consumed.
Are there other use cases for how MDM and SOA, together, add strength to the enterprise architecture? Please add your thoughts by commenting here or on the MDM Community.
Here’s my new monthly column, “MDM Insights”, in the online edition of DM Review.
One of the many “hidden benefits” of a successful master data management (MDM) strategy is the contribution it can make to your enterprise’s move toward a service-oriented architecture (SOA).
Click on “Master Data Management and Service-Oriented Architecture” to continue reading.
Please let me know what you think with your comments here …
And I spoke earlier this week at the New England Oracle SOA Users Group, talking about Master Data Management as a foundation for Service-Oriented Architecture.
MDM initiatives seem to be getting linked to Service-Oriented Architecture or to advanced analytics and business intelligence programs.
I think there can be a problem (but also an opportunity) for MDM in inserting itself between two things that used to talk directly from one to the other (an ERP system to a data warehouse) or (b) asserting itself as a predecessor task to ensure a better outcome (for example, when MDM is used to consolidate and improve the quality of enterprise data before people try to use it in analytics or business intelligence).
While I think it’s true that MDM is in fact needed at most large organizations, having to coordinate with an already-underway SOA initiative, or step back from a planned BI initiative and first tackle MDM, does complicate things a bit. So that’s the “problem” part.
The “opportunity” part is that, for organizations that have the foresight or the luck to tackle MDM first, it makes implementing SOA or achieving business intelligence success that much easier. There’s already a centralized repository of information on customers or products (or whatever domains have been mastered), and that information is proactively managed so that it’s trusted to be accurate, complete, timely and consistent.
Whichever situation your organization is in (tackling MDM first or building it into something else like SOA or advanced analytics), spend the time to develop a workable MDM strategy, using a holistic approach that addresses people, process, technology and information. By all means include an MDM hub in your planning, but make sure you also plan for business process management or sophisticated integration, as well as built-in or bolted-on data quality and enrichment capabilities. And be sure to build a data governance framework around your MDM initiative.
I’ll write a trip report after next week’s DIG conference, to let you know what I thought of the conference itself and whether I got lucky at the tables!
In this article, we’ll give some perspective on the current state of the Master Data Management (MDM) market.
Well-meaning skeptics have raised doubts about whether MDM initiatives have long-term viability, sufficient ROI or in fact, are just another system. This skepticism is, of course, understandable.
Every major new type of enterprise technology, such as Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) goes through an adoption cycle, with early enthusiasm leading to the “Trough of Disillusionment” and eventually, the “Plateau of Productivity”. For more information, see Gartner’s definition of Hype Cycles.
And if you look at the history of MDM solutions over the past few years, the space was very fragmented, initially populated mainly by data quality and matching vendors.
But more recently, some innovations have come together in the MDM space so that it’s starting to offer real value to mainstream companies, not just early adopters.
There have been several innovations on the IT architecture front, such as Service-Oriented Architecture (SOA) and Business Process Execution Language (BPEL), plus new analytics capabilities, improved tools to facilitate data stewardship and more mature MDM hub platforms. All this adds up to a fast-changing landscape.
To add to the momentum, the top enterprise software players (like Oracle, IBM and SAP) have jumped feet first onto the MDM bandwagon, joining the best-of-breed players (like Purisma, Siperian and Initiate Systems) who helped launch the space, giving rise to a whole new ecosystem of system integrators, data service providers and an increasing trend toward global solutions beyond North America.
This growing ecosystem is driving significant growth for the MDM industry as a whole. There are exciting frontiers ahead.
For example, we’re already seeing some business process outsourcing relating to the creation and maintenance of an organization’s master data to an external provider.
At Hub Solution Designs, we’re excited to be part of the MDM wave of adoption from the very beginning. We see more growth, better solutions, and more organizations succeeding with MDM every day.
Please use the Comment button to let us know what you think about the trend towards outsourced data stewardship.
As SOA (service oriented architecture) initiatives gain popularity, let’s look at how MDM (master data management) and data governance can dovetail with a SOA strategy.
SOA, although technically a type of IT architecture, is more of an integrated approach to building high-level services that are inherently reusable and scalable across various applications. High-level services are not consumed as end-point services themselves, but operate more at the business process level.
While composing the entity framework for a service-oriented architecture, a Data Governance Council should be an integral part of the SOA team. The role of the Data Governance Council is two-fold:
- Provide a comprehensive data map (authoritative sources, data flows and underlying data policies) to the SOA architects, and
- To plan and implement “Master Data Services” as part of the services available for consumption to applications within the scope of SOA. An example would be “Create Customer”, where sources, lookups, standards, business validations and enrichments are all built-in, and are available for applications across the enterprise to consume in a robust, auditable fashion.
So what does this do for an MDM initiative?
It provides a powerful platform to integrate the current business processes and to improve levels of data quality, to provide accurate, current and complete data within and outside the IT applications.
It also provides a central platform and process for various domains of master data (suppliers, items, etc) as they come aboard the MDM bandwagon.