Category: IT
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Get an early start for on-time data modeling
I’m a data modeler, so I enjoyed Jonathon Geiger’s recent article entitled “Why Does Data Modeling Take So Long”. But why does he say it like it’s a bad thing? Mr. Geiger’s bottom line is exactly right: “Most of the time spent developing data models is consumed developing or clarifying the requirements and business rules…
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Thoughts after agile training: strengthening values, reducing the cost of honesty, and growing apps
I recently completed ScrumMaster training ably presented by Lyssa Adkins. Throughout the two-day class we appreciated Lyssa’s Zen-like, enabling, style. If her name is familiar, it’s because Ms. Adkins is the author of the book Coaching Agile Teams, one of the leading texts on the subject. I’ve participated on agile projects, but so far only…
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Health care data security: how bad is it?
It is really bad, according to a recent survey by the Ponemon Institute (available here with registration). The white paper, entitled Health Data at Risk in Development: A Call for Data Masking, presents the results of a survey of 492 health care IT professionals on their companies’ practices regarding use of live personal health care…
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But is it art? Skills of the next generation BI professional
There’s a data explosion going on and perhaps the strangest result is that business intelligence analysts need to become more artistic. Recently my friend Ben Harden directed my attention to a post from Steve Bennett of Oz Analytics on the future of BI. One challenge to analysts that Mr. Bennett cited was the unprecedented explosion in data…
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Consider the source in health care data integration
The Atlantic, not typically a technical rag, recently presented an article by business and economics editor Megan McArdle on health care data integration entitled “Paging Dr. Luddite”. The article brings to a mass audience an understanding of both the importance and difficulty of data integration, but the title and general anti-healthcare-professional tone seem counterproductive.
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Special considerations in health care data
I’ve worked with health care data for the past few years, and in a recent conversation I realized it might be valuable to detail some of the complexities of health care data for those who might enter this growing field. Of course these considerations aren’t unique to health care, but they are typical of the…
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Building a writing culture in application development
One of the key skills needed in today’s IT shop is communication, and one of the best ways to improve ability to communicate is to write blog posts and articles. In spite of “IT guy” stereotypes, communication and analytical thinking about business are among the most important skills in application development. Developers, analysts, and managers…
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Agile development: rugby analogy considered harmful
Recently my friend Mark Hudson posted about the inappropriateness of the term “sprint” for an agile project phase, preferring the cycling term “interval.” That post really struck a chord with me. As a rugby union fan and former wing/fullback I’ve always thought the whole rugby analogy was wrong. Agile development is continuous and fluid, yet…
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Metadata goals, ROI, and point solutions
Recently there has been a long, and very interesting, discussion of do-it-yourself versus third-party metadata tools on LinkedIn’s TDWI BI and DW discussion forum (membership required to follow the link). I have followed but haven’t commented, but I suppose I contributed when Information Management kindly published my article on DIY metadata. The discussion is extremely…
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Use conceptual data modeling in requirements definition
I’ve often thought that conceptual data modeling was an underused tool in the arsenal available to requirements analysts, and in a recent conversation I found that many were surprised that it would be used in the requirements phase at all. Checking the Business Analysis Body of Knowledge (BABOK) I found data modeling listed among the…