MDM Architectural Styles: Domains Matter

In a previous blog I discussed the four primary MDM architectural styles: consolidated, registry, coexistence, and transactional. In case you missed it, read it here: MDM Architecture Styles – Do you have the right mix? Each has their individual strengths and weaknesses, but no single MDM architectural style is ideal for every application.  Read more

A Common Explaining Language Leads to Understanding

“I can explain it to you, but I can’t understand it for you.”

A good friend of mine recently alienated the person that pays his salary with the above statement. While you might question his wisdom – I know I did (after a quiet chuckle) – I’m reminded of how often the same thought has gone unsaid when business and IT “collaborate” on traditional data warehouse projects. The business is baffled by the technical jargon that IT uses, and the IT team wishes the business could articulate their requirements in a form from which they can build the solution. The lack of a common language to explain what each side means hinders this understanding. Read more

MDM Architecture Styles – Do you have the right mix?

What is the right MDM architecture style for your organization? It’s definitely an open-ended question that deserves an informed answer, especially before making new investment decisions. But before tackling the question, it is useful to define and understand the MDM styles themselves. Dr. Dave Waddington of The Information Difference defined four broad styles in an article published in Information Management. Read more

Who owns YOUR data?

Implementing an effective Master Data Governance solution can be tough…you have to deal with corporate culture, getting management support, formulation policies, implementing rules and much more. However, a less commonly addressed question is: “Who will own the governed data?” Read more

Why some Data Quality and MDM tools undermine Data Governance

If you ask most people involved with information management and data governance if they understand data quality you would get a resounding “yes!”  However, the true definition of what constitutes quality data is a very complex and subtle one.  Data that is “high quality” for the purpose of, say, operations may be nearly useless for the purpose of invoicing.  In other words, data quality really is relative to the business process that will use the data. Read more

Data Management is a Business Process

I’ve been in and around the data space for over 15 years now, first with Hyperion Software helping finance departments consolidate their financial data. Hyperion understood that Consolidation was a process, not just a set of numbers. We needed to do currency conversions, inter-company eliminations, etc. to deliver a set of financials that could pass regulatory scrutiny. Read more