QlikTech’s QlikView reporting and analysis tool is among a new class of Business Intelligence (BI) software tools. As Ben Harden reported in a recent blog post, BI vendors like SAP, Microsoft, and IBM have traditionally sold “to the IT enterprise, but companies like QlikTech and Tableau are targeting the business and bypassing IT. Their tools are quicker to stand up, more intuitive and don’t need the configuration, support, and hardware that the bigger players require.”

A Quick Overview

At first look QlikView is fairly accessible to those experienced with BI tools. A “.qvw” QlikView file contains three classes of user-facing components: a script-based data integration language that runs when the user requests a “reload”, a data modeling component that looks deceptively like a relational data modeling tool, and a familiar array of data visualizations: graphics, charts, lists, etc.

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What if you could double the efficiency of your software testing process, and substantially reduce errors found during the test, deployment, and maintenance phases, without purchasing any tool or method? The November 28 InformationWeek offers just that in a reprint of a recent Dr. Dobbs article on formal inspections by Capers Jones and Olivier Bonsignour.  They call formal inspections the “defect removal tool of choice” and back up their claim with lots of hard evidence, but I think they are still selling short. Continue reading »

 

I’ve never understood the obsession with “green” status among IT application development project managers, and the intense pressure put on them to “stay green” by the program management offices (PMOs) they report to. We would benefit from a cultural shift away from avoiding yellow status.

For those not in the field, it is in vogue to express IT project status using a stoplight analogy, where green means things are going well, yellow indicates some quality, schedule, or budget risk, and red means there’s imminent risk of failure.

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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 and ensuring that the data structure can be populated by the existing data sources.”  On the projects he describes, no one took time before modeling to determine available data sources and identify business entities of interest, relationships among them, and attributes that describe them before database design started, so the data modeler had to do it.

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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 in a piggish/chickenish role, once in a three-week stint as a consulting architect and twice as the project manager serving as interface to the non-agile organization.

To me Ms. Adkins rocks at making students very introspective and critical of their past project experiences.  These lessons stand out:

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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 data in application testing.

It makes a scary read.  Here are the lowlights: Continue reading »

 

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 quantity to “an almost inconceivable 35 trillion gigabytes” by 2020.  Part of the solution, according to the post, is “actionable insight”, as illustrated by Harry Beck when he created the now-iconic map of the London underground network from the previous rather spaghetti-ish version.  What Mr. Beck did was to distinguish significant from insignificant detail for the intended audience and present that detail in a clear and appealing way.

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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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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 challenges that the new health care application developer or analyst might face. Continue reading »

 

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 require ability to interact effectively with business people, to conceptualize solutions that match business needs, critically evaluate those solutions, and effectively make the case for one of them. Of course this is true of the overall project business case, but more importantly it applies to the daily “IT guy” to business person conversations that happen throughout analysis, design, development, and testing. Continue reading »

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