Many large organizations have finally “seen the light” and are trying to figure out the best way to treat their critical data as the trusted asset it should be. As a result, master data management (MDM) strategies, and the enabling architectures, organizational and governance models, methodologies and technologies that support the delivery of MDM capabilities are…in a word…HOT! But the concept of MDM - and the homegrown or vendor-enabled technologies that attempt to deliver that elusive “single version of truth”, “golden record”, or “360-degree view” - has been around for decades in one form or another (e.g., data warehousing, BI, data quality, EII, CRM, ERP, etc. have all at one time or another promised to deliver that single version of truth in one form or another).
The current market view of MDM has matured significantly over the past 5 years, and today many organizations are on their way to successfully delivering multi-domain/multi-form master data solutions across various physical and federated architectural approaches. But the long-term evolution of the MDM concept is far from over. There remains a tremendous gap in what limited business value most MDM efforts deliver today compared to what all MDM and data management evangelists feel MDM is capable of delivering in terms of business optimization, risk mitigation, and competitive differentiation.
What will the next evolution of the MDM concept look like in the next 3, 5 and 10 years? Will the next breakthrough be one that’s focused on technology enablement? How about information architecture? Data governance and stewardship? Alignment with other enterprise IT and business strategies?
As Forrester’s lead analyst on data warehousing (DW), my core job often involves diagnosing enterprise analytics practitioners’ DW aches and pains. I try to cultivate a reassuring bedside manner and give them something for both immediate and long-term relief from their problems.
I receive all Forrester customer inquiries on DW matters, many of which are from IT practitioners who have hit a wall of intractable technical, operational, or vendor-related issues. Those sessions usually involve me probing for the source of the IT practitioner’s DW-relevant woes. If all of these issues could be isolated to the DW itself, my life would be much easier. But customers’ DW concerns are often tangled into stubborn knots of business intelligence (BI), master data management (MDM), data integration, data governance, business process management, IT service management, and other critical infrastructure, operations, and application issues. Often a seemingly DW-based problem such as poor-performance queries reveals that the root cause is somewhere else entirely, and the DW itself is the least of their problems.
Broadens the definition of metadata beyond “data on data” to include business rules, process models, application parameters, application rights, and policies.
Provides guidance to help evangelize to the business the importance of metadata, not by talking about metadata but by pointing out the value it provides against risks.
Recommends demonstrating to IT the transversality of metadata to IT internal siloed systems.
Advocates extending data governance to include metadata. The main impact of data governance should be to build the life cycle for metadata, but data governance evangelists reserve little concern for metadata at this point.
I will co-author the next document on metadata with Gene Leganza; this document will develop the next practice metadata architecture based partially but not only on a metadata exchange infrastructure. For a lot of people, metadata architecture is a Holy Grail. The upcoming document will demonstrate that metadata architecture will become an important step to ease the trend called “industrialization of IT,” sometimes also called “ERP for IT” or “Lean IT.”
In preparation for this upcoming document, please share with us your own experiences in bringing more attention to metadata.
I just read a great blog post by Marty Moseley discussing the results of a data governance survey he and his team recently fielded. The feedback he collected matches recent data-governance-related surveys and interviews I've done with my clients at Forrester - the general consensus being that most data governance programs - if they exist at all - remain extremely immature and fraught with risks. The most common roadblocks range from minimal to no executive sponsorship (as Marty also noted), IT-driven efforts with limited to no business participation, lack of business justification and the ever-present likelihood of "de-prioritization" when a more compelling initiative or fire drill comes along.