Firstly, the questions from users regarding cloud computing are MDM are really tentative at best.  There are not many users seriously considering moving their entire data management efforts to the cloud.  One has to remember, MDM is as much about application information governance, so unless those applications reside in the cloud, moving data outside of the firewall simply adds more complexity.

Secondly, there is various data management services offered via on-demand, SaaS, or cloud, and these can help some of the technology aspects of MDM.  I am thinking specifically of data quality services.  These data quality services might be used for all manner of information management, but they could also be “called” by an application residing behind the firewall, in order to send select data “outside” for processing, upon which it is “returned” to the business.  Another aspect of MDM that is far more mature (since it existed before MDM did) was the idea of data enrichment and validation.  Several vendors and services offer a means to validate a customer credit worthiness, or provide additional data concerning a customer or product in order to enhance a specific business processes.  So “cloud” and MDM are friends already, but is “MDM” really destined for the cloud in its entirety?

Gartner’s position has been clear – yes, over time, selectively.  But there are numerous barriers.  The technology is not really a barrier – it is more of a challenge.  The real barriers are well documented – spanning clear line of sight to business case and business sponsor, change management, establishment of governance and so on.  So a cloud-based MDM offering does seem to offer some benefits, in removing some of the more tactical IT challenges, but does it alone help make the real barriers easier to overcome?  I wonder.

Though the physical hosting of data and data processing may reside on servers in the cloud, that is very different from re-locating the business role of data stewardship from

The physical hosting of data and data processing may reside on servers in the cloud, but that is very different from re-locating the business role of data stewardship from business users (behind the firewall) to some 3^rd party.  And can that third party be synonymous – which is the whole point about CPU capability in the cloud?  I doubt it.  Some years ago i2 Technologies implemented a unique solution for Vendor Managed Inventory (VMI).  They delivered what became a managed supply chain services whereby their employees did much of the planning processes for Panasonic as it maintained superior services levels for its TV’s through its retail channel partners like Best Buy.  This was years ago (though it may still be operating today), and the technology was hosted and operated by i2 but could have claimed that this was a cloud based solution, coupled with managed services.  Though innovative i2 was never able to monetize this idea well – the actual solution ended up being so unique in its work that it could be sold  “as is” not least because most other prospects where not willing to ‘give up’ that level of control on what was, in essence, a source of differentiation in the market place.  This could be what happens with “stewardship in the cloud”.

Overall though this new cloud offering will help the adoption of MDM.  Setting up some of the technology needed to support an MDM program looks easier to do, so more organizations can “kick the can” and see how it looks.  Perhaps some organizations will “play” with MDM and then “upgrade” to a real one later – not unlike Talend’s idea with its Community Edition-based MDM, Open Source Software solution, that has a logical “upgrade” path to that vendors Enterprise Edition.  But will large enterprise actually seek out full blown cloud-based MDM offering?  Or will this better suit smaller/mid-sized enterprise?

It would seem that Open Source Software and cloud Computing are set to impact the MDM market, but the question is, by how much and how soon?

By the way, Orchestra Networks have a cool video that coincides with today’s announcement: http://www.youtube.com/user/smartdatagovernance

We have been using the term best-of-breed, specialist, or niche MDM vendor to denote a vendor that has focused on one specific master data domain.  The two most common data domains referred to by users is customer, and product.  One side bar that always get’s my goat: does a customer focused enterprise always start with MDM of Customer data?  The answer is a firm, “no!”  A customer focused firm that sells product and/or services may have reasons to start with MDM of Product data.  After all, if you don’t know exactly what it is you have to sell, how can you assure good customer service?  But I digress…

Best-of-breed MDM has not necessarily implied single industry focus.  It so happens that a focus on a specific domain generally leads to a focus on one or a small number of industries.  It seems that the greatest gap in terms of IP exists between customer and product domains, rather than any two industries.  However, best-of-breed MDM does mean “depth” in terms of functional capability to meet the needs of that domain/industry.  And given the number of end users I and my colleagues have spoken with so far, there is a huge, wide discrepancy in the complexity of issues customer face with MDM.  

Another characterization of best of breed MDM is that the vendor focuses on what we call operational MDM.  Operational MDM is form of MDM that explicitly seeks, as part of its governance routines, to clean up source data once errors are found in the business. 

Analytical MDM represents a form of MDM that exists in a BI context, to support cleansing of data in a data warehouse environment, where there is no explicit desire to clean up the source data.  I came up with the idea of analytical MDM to highlight the overlapping in technology and technique (use of data quality, cleansing, normalization etc) and differences (desire to clean source; not to clean source) across a continuum of use cases.  Though not accepted early on it seems that the term, and differences, is now widely accepted.

So what is a generalist MDM vendor?  There are in fact different types of generalists.  One might focus on analytical MDM only.  This means that the technology is used to model all kinds of master data (product, customer, person, hierarchy, and dimension data) but in a BI environment only.  Another might be a vendor that focuses on operational MDM but for many different types of data domain, though the functional capability for any one domain is not that “deep”.  

Users have to decide what they need to focus on – and this may change over time.  Business drivers may lead to the recognition that “deep MDM” skills are needed first hand to get to grips with very complex product data workflows, but later, a more general approach is needed to master other domains.  

So the need will change over time; and the vendors capability will evolve also.  As such, there is no “right” position to take.  Both, and all the variations in between, have a role to play in meeting user requirements.  The key perhaps is to align the right vendor approach to the need.

Of course, putting my vendor hat on, I have to answer, “But which vendor will win?”  It depends – on what we mean by “winning”!