Data Governance Roundtable
Late breaking news: Dan Power from Hub Designs will be appearing in a “Data Governance Roundtable” tomorrow (Thursday, December 1st at 11:00 am EST / 10:00 am CST / 8:00 am PST). Read more 
Oracle’s MDM Strategy and Roadmap
At the Oracle Applications Users Group (OAUG) COLLABORATE 2010 conference this week, I attended a session by Pascal Laik, Oracle’s VP of Master Data Management Strategy.
He started out by talking about several Oracle MDM customers, their success stories and their return on investment, across drivers like growth, efficiency, improved IT agility, and compliance.
Pascal moved on to talk about MDM implementation challenges. Oracle surveys its MDM customers every two years. Measuring actual ROI achieved is the most difficult challenge reported. Next is breaking down organizational silos, and then demonstrating incremental business value.
Five out of the top ten challenges were related to data governance and project/organization. These were big themes two years ago as well. So Oracle worked with an outside partner on the areas of strategy, policies & processes, organization, measurement & monitoring, technology, and communication. They got a group of 10-15 customers together 2-3 times per year, and that group put together a set of requirements for a product that Oracle has now created called Data Governance Manager. This product helps data governance professionals to operate and monitor the hub and to define and enforce policies.
Pascal showed a short video from an Oracle customer, Areva. Their program was called STOCK – Strategic and Operational Customer Knowledge, to ensure the high quality of customer data. They used a five step approach: Collect, Harmonize, Merge, Enrich, and Publish. The benefits included saving employees time, ensuring that internal people can rely on customer and prospect data, and providing the entire enterprise with a clear vision of the customer database.
The second set of challenges related to ROI and business case – measuring actual ROI achieved. Oracle now has a web-based ROI model available through its sales team. Oracle also has a group of people that do a 3-5 week management consulting exercise called “Insight” that delivers a full business case.
The third set of challenges is the first one involving technical issues: #10 and #11 (integration and data quality).
Two years ago, the #1 issue was procuring skilled resources. So Oracle has been working closely with systems integrators, so now this issue is down to #7. Integration with operational applications has gone from #2 to #11.
Lastly, Pascal discussed Oracle solutions, investments and its strategy going forward. Oracle now has Customer Hub, Supplier Hub, Product Hub, and Site Hub. Data Relationship Management, which is a financial hub to manage financial entities such as the chart of accounts and other hierarchies, is also an analytical hub.
Oracle Customer Hub (formerly known as Universal Customer Master) is now on release 8.2, which shipped in January 2010, and includes the new Data Governance Manager module. This is the largest customer release in four years.
Oracle’s MDM strategy has two legs – embedded “best in class”. Oracle has OEM’d the Informatica solution, using the Identity Systems solution (now owned by Informatica) and the Address Doctor solution (also from Informatica) for postal cleansing for 200+ countries. The other leg is “open” – Oracle is providing a “Universal DQ Connector” for selected vendors like Trillium, Acxiom, D&B and Datanomic. (Note: the embedded “best in class” approach is somewhat controversial, since Informatica is now competing directly with Oracle, since it has acquired the Siperian MDM hub).
The end-to-end data quality framework (the Data Quality “Machine”) has a Rules Manager for design, development and validation (IDQ). There is a process (Analyze/Profile, Standardize/Cleanse, Match & De-Duplicate, Enrich) with a Scorecard & Reporting, and an Exception Management Process. The output is to load the MDM system with zero rejects.
Oracle has also acquired Silver Creek Systems, which is focused on product data quality. It is a self-learning semantic engine to handle the complexities of product information.
Pascal talked about some of the newer MDM hubs, Supplier Hub and Site Hub. Site Hub in particular has experienced strong interest from retailers, fast food companies and large enterprises, which are using it to manage stores and locations.
Oracle’s MDM investments are critical for Oracle in terms of its differentiation strategy, and data governance is the number one item from its customer advisory board. Oracle has reached 1,000 MDM customers across all of its various MDM products.
Pascal wrapped up by talking about how competitive the MDM space is and the recent acquisitions in the market. Oracle’s history is in applications. Oracle brings a pre-built, flexible schema with enterprise-grade, verticalized hub applications. Oracle MDM hubs are pre-integrated with both Oracle and non-Oracle applications. And Oracle provides best-in-class data quality and data governance solutions.
Consolidation of Data Quality and Data Integration
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In a recent article, we covered the importance of data integration to Master Data Management (MDM).
This article elaborates on that in the context of today’s software market, and talks about how the visionary data integration vendors are scrambling to acquire and offer data quality as part of their integration suites.
Historically, data quality initiatives have been rolled out only on a project-by-project basis, while integration initiatives have been point-to-point application integration projects.
But more recently, as MDM programs have started gaining momentum, there is a need being felt in the marketplace for a single platform that can integrate data from multiple sources across the enterprise (web, data warehouse, ERP, CRM, legacy systems and systems from acquired companies) as well as run sophisticated data quality processes on these sources.
This requirement allows for a single administration console and metadata repository, as well as common transformations, user interface and a unified developer workbench, all on a single, combined integration and data quality platform.
This vision is consistent with moving towards a Service-Oriented Architecture as well, and is very conducive to providing a single environment for “data as a service” that is trusted and consistent across sources.
The customer tends to love it, since an integrated platform like this generally implies lower Total Cost of Ownership and smaller IT costs than standalone integration and data quality investments, and more rapid software development cycles.
The MDM vendor, if not providing such a platform itself, loves it since it can focus on what it does best, i.e. matching, merging and building data hierarchy.
Recognizing the above need, California-based Informatica Corporation acquired identity resolution vendor Identity Systems, while Massachusetts-based Trillium Software acquired address cleansing vendor Global Address. These are just two examples of recent data integration and data quality market convergence.
And the acquisition of Group 1 Software by Pitney Bowes provides more evidence of this shift. In the process, niche data quality players are finding it more difficult to compete in such a dynamic marketplace.
If you’re considering acquiring a data quality tool for a corporate initiative, consider the above dynamics. And we’d love to hear your thoughts via comments on this article.
