If you are anything like me, as a data professional you’ve experienced many frustrations in your career due primarily to things that have occurred or choices that were made long before you were around (over which you had no influence and with which you must now live). However, with the recent popularity of service oriented application development, we now have a chance to lay a solid foundation when it comes to providing data services: one that will eliminate ambiguity around sourcing and meaning, one that provides a framework for consistently applying data management principles, and one that will enable the promise of a service oriented architecture (SOA).

Some of the presenters from EDW 2010 are participating in a series of Webcasts related to topics that will be covered in more depth at the event.  Each Webcast is about one hour in length and is recorded. 

Data governance is one of those topics that many people agree to talk about, explore, and even implement.  However, when you ask for a definition, you get many different answers.  Often you will get a sort of “I know it when I see it” reply.  This answer is not conducive to success.  Businesses and organizations prefer to deal with topics that offer solutions to problem or exploit opportunities.  Part of the bad reputation of internal IT departments is due to the perception of fad-hopping.  Repositories, data warehousing, and information engineering are all topics that went through a bit of hashing about before the dust cleared. It goes without saying that all three developed perceptions of ‘failure to deliver’ at the CXO level.  Often the success stories of a particular topic were intertwined with a business project, and discerning the exact role of the technology was difficult.  The definition of the technology often varies across success stories as well.

Integration solutions are often classified as Enterprise Application Integration (EAI). However, if we think deeply about the examples previously provided, I suggest that this is an incorrect classification. The problem is less about the applications and more about sharing and reusing the underlying data.

A friend of mine - we’ll call her Jane - is a psychiatrist.  A few years ago, she was at dinner with a couple she had known for many years.  The conversation had been dominated by the problems they were having with their adolescent kids.  Finally she could hold back no longer.  “Look,” she said, “I’m a professional in this field and I know I shouldn’t tell you what to do, but you’re doing some very specific things wrong…” 

In my last column, I related the story of my friend “Jane” the psychiatrist who, in a moment of weakness, criticized the way that her friends were bringing up their teenage kids, and offered some free advice on how to do it better.  Needless to say, the advice was not taken and the friendship suffered.  After drawing some lessons for consultants, I concluded with a question: If you were the parents of those troubled adolescents, what would you have liked Jane to do?

Technology innovations are enabling sophisticated data strategies with the potential to reshape products, upend customer relationships, and transform the role of the IT organization.  This four part series explores (1) the new context, (2) the opportunities enabled, (3) the implication on trust and customer relationships and (4) the implications for the IT organization.  The series concludes with a 90-day plan for a purposeful and systematic analysis of the opportunities and risks.

Part of the EDJ mission is research.  This includes surveys as to who is doing what and whether or not they are having any success.  Our survey for SOA was sent to our Best Practices Council, a growing body of technology users and beneficiaries.  Below is our detailed presentation of the findings, and a recap of responses.  However, for the time constrained reader, I’ll present a summary.

Perusing the published literature on Master Data Management (MDM), as well as reading press releases, news stories, and listening to case studies and assorted podcasts and web seminars, it is not unusual to come across the phrase “golden copy” in reference to the result of a master data consolidation activity. Presumably, the term “golden copy” implies a record that epitomizes the highest quality information, on which any application can depend. The expectation is that the data integration and consolidation features of the MDM program are able to absorb all the various and sundry records from across the enterprise into this perfect data set.

Data Are Assets

An exercise popular in many training courses goes something like this.  The class is asked to imagine a fine antique French desk, recently purchased for $20,000.  Atop the desk sits a brand new laptop computer, complete with all the bells and whistles, that cost $3,000, and a compact disk that cost thirty cents.  The CD contains the only known list of the names and purchases of the organization’s fifty largest customers.  Now, the exercise goes, a fire has started and you can only save one of the three.  Which do you save?

The EIM survey (Part 1)  was sent to several thousand CIOs and other information professionals, as well as business managers.  We will have a second survey later this year, with more details.  This go-around we were looking for the macro-level influences and thoughts. 

As usual there is always a finding or two that raises an eyebrow.  We supplied a simple definition of EIM and asked if ayone was doing it – and we got a glass half-empty half-full response.

Consider for a moment the balance sheets of companies such as Experian, Trans-Union, Acxiom and Choicepoint.  The primary product these organizations produce, inventory and sell is not represented in their book valuation at all.  These companies collect, generate and sell information.  But the primary item that these and other businesses increasingly proffer cannot, by current accounting standards, be represented financially.  Yes, we can represent the cost to acquire, generate and manage information, including the bountiful disk farms holding these terabytes of data.  But imagine The Gap or General Motors being unable to account for their inventory of clothing and fabric, or cars and auto parts.