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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In the past I’ve never understood what people really mean they say “think outside the box” but Jim Harris, in a recent OCDQ blog post, helped me figure it out.

Mr. Harris ends with this provocative line: “the bottom line is Google and Facebook have socialized data in order to capitalize data as a true corporate asset.”  The post starts with a cold war analogy and proceeds to describe how Facebook and Google have made big money as “internet advertising agencies:” offering free services with which users (like us) serve up personal data in return for use of the service, then selling advertising space based on our data (hopefully anonymized).

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Who would want to be a national health care administrator?  Who would want the responsibility for managing health care and formulating health policy for tens or hundreds of millions of people?  It seems obvious that such decisions would rely on quality data.  A recent interview impressed upon me how much data managers can learn from a field where data recording millions of separate life and death decisions aggregates to support decisions on the future allocation of health care resources.

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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 »

 

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 the agile originators chose the word “scrum” for its daily standup meetings.  In rugby union a scrum is a set play resulting from a minor penalty, like offside in American football or a foot fault in tennis.  If you like the rugby analogy the right term would have been “ruck,” which is kind of like a scrum but part of the continuous run of play (in the other kind of rugby, called rugby league, the scrum has devolved into an almost meaningless stylized ritual – which I guess happens on some agile projects). Continue reading »

 

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 informative, presenting the views of a variety of knowledgeable professionals in different situations, and describing successful and sometimes not-so-successful efforts to solve the essential metadata challenge: how to document what information is locked up in databases. Continue reading »

 

“Our goals can only be reached through a vehicle of a plan, in which we must fervently believe, and upon which we must vigorously act. There is no other route to success.” – Pablo Picasso

It is an old story: about 30% of IT application projects succeed, 45% are “challenged,” and the other quarter fail altogether.   That’s the consistent result over the years of the Standish Group Study of Project Outcomes.  Jorge Dominguez, here, displays a chart of the remarkably similar results since 1994.  Not a pretty picture, right?  Some question the validity of the Standish studies, but Scott Ambler parallels the Standish story in a recent Dr Dobbs column called “Lies, Great Lies, and Software Development Project Plans,” which itemizes the strategies commonly used by IT project managers to “stay out of trouble” when schedule/budget results don’t match initial estimates.  For example, “18% change the original schedule to reflect the actual results”. Continue reading »

 

Information Management recently sent around their pick of best IM blog articles of 2009.  Among them was Forrester’s James Kobelius’s reaction to Bill Inmon’s “incineration of a straw man concept that he refers to as ‘virtual data warehousing (DW).’”

According to Mr. Inmon, virtual data warehousing reminds him of the carnival game called whac-a-mole.  He says “just when you think this incredibly inane idea has died and just when someone has delivered what should have been a deathly blow, out it pops again from another hole.” Continue reading »

 

Elements of IT Architecture

Many see IT as application of technology to solve business problems.

Of course, this is true but it leaves out the third element, which is to apply the right architectural pattern to solve the problem.  For example, when the business problem is that reporting is slow and reports from different departments don’t match, the astute IT professional immediately thinks in terms of a data warehousing pattern employing technologies like databases, extract-transform-load (ETL) tools, and multi-dimensional reporting suites. Continue reading »

 

Today, the foundation of most of our custom-built systems is a relational dbms.  While development frameworks vary, they overwhelmingly access and maintain data in relational tables and columns.  As I write I routinely save this post in a MySQL database, and at work I tend SQL Server applications.  Millions of others develop, use, and extract analytical data from thousands of SQL Server, DB2, and Oracle applications, on servers and networks maintained in-house by in-house administrators. Continue reading »

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