Recently on dm-discuss there was a posting about the Wolfram|Alpha technology, currently in development, which is a Computational Knowledge Engine. The initial question, posted by Tony Shaw, was whether or not this technology would replace Google as our preferred search engine. I, along with others, wondered ho this engine would deal with the confusing semantics of  language.  For instance, if I asked a computer the question:

How many Jobs are there at Apple?

would the computer know if I was asking about how many people named Jobs?  How many open positions?  How many positions, open or filled?  How many project tasks?  Construction jobs?  Would it guess whether or not I meant Apple Records, Apple, Inc, or a local Apple Store?

Since the Wolfram|Alpha technology is based on Mathematica, it actually calculates answers instead of just returning search results.  See this Harvard Berkmam Center video, which I wish showed the screen more than Wolfram:

I still see a huge need to conquer the issue of semantics and the nuances of language.  Indeed, there are other bloggers who are pointing out some of the issues that must be addressed.  I especially liked Jon Stokes' post in ars technica:

In the end, any good humanist, scientist, or journalist knows how hard it is just to assemble a reliable and relevant set of facts, much less to take the next step and synthesize those facts into understanding, and then communicate that understanding to an interested reader.

I'm very happy to see innovation and research in the areas of making massive amounts of data accessible and usable to the general population.  From what I've seen (very little) of Wolfram|Alpha, we are making great progress in that direction.  I just wish people, even brilliant people, would clue in to the fact the trip from data to fact to knowledge is not something that can be easily automated.  Nor can it be accomplished just with good column names or mathematical formulas.  A good data architect knows this because we've spent decades trying to get 3 people at the same organization at the same time to agree what we mean by Customer or Revenue. I can't imagine trying to do that for all people, in any culture, at any company, across the globe.

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Karen Lopez: Musings on Data, Process, and Architecture Reading, Watching and Listening

I've been busy for the last few weeks updating e-mail addresses & subscriptions on our Discussion Groups.  Some of these updates are due to people upgrading their jobs (Congratulations!) and others have been due to people involuntarily separated from their jobs (Keep a positive attitude!).

I know that these are scary times for everyone: the employed, the worried about being employed and those who are researching new job opportunities.  I have been developing presentation materials and articles about ensuring career successes in data management. My first demonstration of this was my recent event at DAMA Iowa. That went very well, so we are working on expanding it for a more in-depth workshop.

We have also been waiving job posting fees for direct hiring organizations to our Groups so that we can help our community members find new projects.

In the mean time, I think reviewing this video on Slate would be helpful in boosting morale as well as helping you pick the right responses for your exit interviews.

You might also want to search for Lester Burnham's (Kevin Spacey) resignation letter from American Beauty. It's Not Safe For Work (NSFW), but it does have its moments.

Happy viewing.

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Karen Lopez: Musings on Data, Process, and Architecture Reading, Watching and Listening

Joe Bugajski, blogger at Analysis from the Bottom Up, has written about his experiences in an Emergency room.  Reading through his post is chilling, especially when he points out that an underlying data model may have been at fault.

Electronic Health Information Systems

Medical personnel at urgent care and the hospital who interacted with me all used a version of the same electronic health information system (the “system”). It became clear that everyone was fighting that system. Indeed, they wasted between 40% and 60% of their time making the system do something useful for them. The system kept everyone from fulfilling their duties - the health information system did not help medical professionals perform their duties.

Since my hospital stay, I confirmed that electronic health information systems are mostly broken. I interviewed medical professionals, healthcare IT experts, and my allergist. They confirmed my sickbed analysis. Indeed, several experts said that they longed for handwritten charts once more hanging from the foot of every patient’s bed. (Again, please read Prof. Dr. Armstrong-Coben’s Op-Ed article.) My analysis argues for careful analysis of strengths, weaknesses, opportunities, and threats (SWOT) associated with building a national health information network. If the nation simply accepts the President’s vision while healthcare IT vendors collect some of the $20 billion stimulus bounty, individuals and businesses will pay higher medical costs, patients will receive inferior care, and medical professionals will lose precious time fighting IT systems instead of delivering better care.

Killer Data Model

Poor data model design deters medical professionals from delivering quality care....

What is especially valuable, though, is reading through the comments (including my own), to Joe's blog post.  The range from emergency medical doctors, hospital IT pros, other IT pros, other patients.  There is discussion going on, via the comments, that we rarely see when we discuss the complex problems resulting in poorly designed and poorly used systems.  There are no quick and single point solutions to the problem Joe faced in his trip to the ER.

Put aside some time to read his post and the wealth of knowledge being captured in the blog comments.

Analysis from the Bottom Up | The Data Model That Nearly Killed Me

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Karen Lopez: Musings on Data, Process, and Architecture Reading, Watching and Listening

Michael Krigsman has written over at ZDNet.com an insightful post about business users who seem to want all the benefits of great technology, but they want it at no cost and with no change to their world.

I've seen this over and over in my career.  Clients expect to have improved data quality, but they want "IT" systems to fix their data quality problem without any changes to their data acquisition, data entry, data planning, or data movement processes.  They do seemingly want to have Chuck Norris come in and stare down/intimidate their data into becoming great information.

Brian defines the essence of Chuck Norris Syndrome when he acknowledges that some people believe:

"Chuck Norris can fix everything without changing anything."

I don't know how to get something for nothing.  If I did, I'd be the wealthiest person on the planet.

I do identify processes, tools, and procedures that clients can use to get more value out of their data.  An organization cannot improve the quality of their data with no changes at all.  It's sort of like the laws of nature: if you want improvements, something has to change.  If you use the same recipe, you get the same bread.

I follow Michael on Twitter.  You should, too.  And you should definitely follow his posts at ZDNet.com.  Our "profession" is one that does not study and promote the sharing of project failures.  That means we aren't really professionals, yet.  Michael's work in this area is a step in the right direction.

Chuck Norris Syndrome and IT failure | IT Project Failures | ZDNet.com

Technorati Tags: Project,IT,Failure

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Karen Lopez: Musings on Data, Process, and Architecture Reading, Watching and Listening

Corey Smith, an IS manager, has a great post about age, experience, and keeping data management relevant to all generations of IT professionals...and vice versa:

Let me leave you with one final thought. Data management is both a set of activities and a profession. Many people who do the former don't consider themselves the latter. They are, nevertheless, contributing to the body of knowledge, for better or worse, and we need to connect with them just as much as an up-and-coming metadata analyst. Consider the outcomes that Mrs. AdvisoryBored identified in her original proposal for the Business Information Management class (MGMT 215) at Edmonds Community College (see the end of page two). There is no guarantee that the students, particularly those from the Business department, will embrace those data management principles and/or the profession, but she has at least had the opportunity to introduce the concept of data as a managed enterprise resource.

Check out his blog for other interesting and thought-provoking takes on IT and data management.

Advisory Bored: The Data Model of Dorian Gray