What I Learned About Data Management in Japan

December 6, 2011

I just returned from speaking at the DAMA Japan conference. A couple of the officers saw a presentation I gave at the DAMA International conference last April on performing Data Management maturity capability assessments and they asked me to repeat the speech at their conference in Tokyo.  The Data Management Association (DAMA dama.org) created a Body of Knowledge document in 2009 (DMBOK) that was translated into Japanese in 2010.  This conference had a lot of focus on the DMBOK, and so they were very interested in how I had been using it to assess Data Management maturity for our client organizations.  About 90 people attended my presentation. The people at the conference and the DAMA Japan organization were very interested in measuring how well their organizations were doing with Data Management, especially against how other organizations are doing.

One thing I learned during the conference was how they were using the “three R’s” concept: “reuse, recycle, reduce” concerning Data Management and adding a fourth “R” for “respect”.  In organizational data it is generally agreed that 80% or more of an organization’s data is ROT: redundant, out-dated, or trivial.  More of our planning time should be spent trying to reuse or remove data structures than on trying to create new data structures.  They had added an extra “R” to “reuse, recycle, and reduce” to stand for “respect”, a very Japanese consideration and always worth attention.

Another thing that I learned is that some of my Japanese colleagues will take a day to have a brainstorming session on different IT and strategy concepts, which sessions might very well happen in a hot spring or bath house.  Concerning Enterprise Architecture, they had recently had such a session and decided that it was critical that Enterprise Architecture include business innovation, employee motivation, and technology innovation.  This summary was shared with me after we had all consumed a great deal of sake and other alcohol and they were very willing to try to share their ideas in English.

The people I met at the Data Management conference seemed not very interested in Data Governance but, as I said extremely interested in assessing Data Management practices.  And it appears that adding a banquet or hot bath makes the discussion of data management and strategy even more insightful.

The Problem With Point to Point Interfaces

November 21, 2011


The average corporate computing environment is comprised of hundreds to thousands of disparate and changing computer systems that have been built, purchased, and acquired.  The data from these various systems needs to be  integrated for reporting and analysis, shared for business transaction processing, and converted from one system format to another when old systems are replaced and new systems are acquired.  Effectively managing the data passing between systems is a major challenge and concern for every Information Technology organization.


Most Data Management focus is around data stored in structures such as databases and files, and a much smaller focus on the data flowing between and around the data structures.  Yet, because of the prevalence of purchasing rather than building application solutions, the management of the “data in motion” in organizations is rapidly becoming one of the main concerns for business and IT management.  As additional systems are added into an organization’s portfolio the complexity of the interfaces between the systems grows dramatically, making management of those interfaces overwhelming.


Traditional interface development quickly leads to a level of complexity that is unmanageable.  If there is one interface between every system in an application portfolio and “n” is the number of applications in the portfolio, then there will be approximately (n-1)2 / 2 interface connections.  In practice, not every system needs to interface with every other, but there may be multiple interfaces between systems for different types of data or needs.  This means for a manager of application systems that if they are managing 101 applications then there may be something like 5,000 interfaces.  A portfolio of 1001 applications may provide 500,000 interfaces to manage.  There are more manageable approaches to interface development than the traditional “point to point” data integration solutions that generate this type of complexity.


The use of a “hub and spoke” rather than “point to point” approach to interfaces changes the level of complexity of managing interfaces from exponential to linear.  The basic idea is to create a central data hub.  Instead of the need to translate from each system to every other system in the portfolio, interfaces only need to translate from the source system to the hub and then from the hub to the target system.  When a new system is added to the portfolio it is only necessary to add translations from the new system to the hub and from the hub back to the new system.  Translations to all the other systems already exist. This architectural technique to interface design makes a substantial difference to the complexity of managing an IT systems portfolio, and yet it had nothing really to do with introducing a new technology.


If the Data Quality got better but no one measured …

November 2, 2011

There is an old philosophical question: “If a tree fell in the forest but no one heard it, did it make a noise?”  The basis of the question being that every time we’ve seen a tree fall in the past it has made a noise, but if no one heard it fall then maybe this one time it didn’t … but you couldn’t prove it either way.

Centrally important to certain areas of Data Management such as Data Governance, Master Data Management, and especially Data Quality is the absolute importance of metrics and measures.  You can’t demonstrate that the quality of data improved unless you measure it.  You can’t report the benefit of your program unless you measure it.  And, showing improvement means that you need to measure both before and after to calculate the improvement.

Senior executives in organizations want to know what value a technology investment brings them.  And the ways to show value are increased revenue, lowered cost,  and reduced risk (which can include regulatory compliance). Without reporting financial benefit to management few organizations are willing to support ongoing improvement projects for multiple years.  Also, it is important to report both what the financial benefit has been and what additional opportunities remain – management is very happy to  declare success and terminate the program unless you are also reporting what remains to be done.

Show Me the Money! – Monetizing Data Management

October 23, 2011

On November 10 Dr. Peter Aiken will be coming to Northern NJ to speak at the DAMA NJ meeting about “Monetizing Data Management” – understanding the value of Data Management initiatives to an organization and the cost of not making Data Management investment. http://www.dama-nj.com/

At Data Management conferences I’ve been to over the last few years people are still more likely to attend sessions on improving data modeling techniques than on valuing data assets or data management investment, or the cost of poor quality data.  Maybe it’s just the nature of the conferences I attend, more technical than business oriented.  But I think every information technology professional should be prepared to explain, when asked or given the opportunity, why these investments are imperative.

If you can make it to Berkeley Heights on November 10, I hope you will attend Dr. Aiken’s presentation, which you will find to be a great use of your time.