Category: App Dev
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Escaping Teradata Purgatory (Select Failed. [2646] No more spool space)
Also see the related post More on “Select Failed. [2646] No more spool space” If you are a SQL developer or data analyst working with Teradata, it is likely you’ve gotten this error message: “Select Failed. [2646] No more spool space”. Roughly speaking, Teradata “spool” is the space DBAs assign to each user account as…
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Reporting Database Design Guidelines: Dimensional Values and Strategies
I recently found myself in a series of conversations in which I needed to make a case for dimensional data modeling. The discussions involved a group of highly skilled data architects who were surely familiar with dimensional techniques but didn’t see them as the best solution in the case at hand. I thought it would…
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Analytics Requirements: Avoid a Y2.xK Crisis
Even though it happens annually, teams building new visualizations often forget to think about the effects of turning over from one year to another. In today’s fast paced, Agile world, requirements for even the most critical dashboards and visualizations tend to evolve, and development often proceeds iteratively from a scratchpad sketch through successively more detailed…
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Protect Your Culture: Screening for authoritarian project leaders
It’s fashionable today to talk about the risks of authoritarianism in the political sphere. I’m not going to speculate on that, but such talk got me thinking about the same tendencies among IT project leaders. What is an authoritarian personality? (Yes, that’s actually a thing.) Is it truly antithetical to a healthy project? If so, how…
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More on the Agile Architect: Process and Knowledge Transfer
I’ve written about groupthink-related quality challenges on Agile projects, and the architect’s role in preventing groupthink from degrading quality. I’ve seen other risks related to the cohesion and potential insularity of successful Agile teams, and the architect is also well positioned to help prevent these: a tendency to neglect setting up and documenting repeatable processes, and a…
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Assumptions: A Key to Technical Leadership
There’s an unfortunate and rather rude saying about assumptions that I’ve found popular among IT folks I’ve worked with. I say unfortunate because, to me, assumptions that are recognized early and handled the right way are a key to successful projects. Technical players who use assumptions well can help set projects on the right path…
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GIGO: Data Quality Guidelines for Application Development
There’s consensus among data quality experts that, generally speaking data quality is pretty much bad (here, here, and here). Data quality approaches generally focus on profiling, managing, and correcting data after it is already in the system. This makes sense in a data science or warehousing context, which is often where quality problems surface. To quote William…
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Lynchburg SQL Server User’s Group 10/30
Yesterday I had the pleasure of presenting “The Business End of Data Modeling” for the Lynchburg SQL Server User’s Group. It was a great time, thanks for having me out! I’ve linked the presentation below, please comment here or shoot me an email if you have comments or questions. BusinessEndOfDataModeling20141030
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Get Business Requirements Right by Resolving Many-to-Manys
Logical data modeling is one of my tools of choice in business analysis and requirements definition. That’s not particularly unusual – the BABOK (Business Analysis Body of Knowledge) recognizes the Entity-Relationship Diagram (ERD) as a business analysis tool, and for many organizations it’s a non-optional part of requirements document templates. In practice, however, data models…
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A Field Guide to Overloaded Data
At the very first TDWI Conference, Duane Hufford described a phenomenon he called “embedded data”, now more commonly called “overloaded data”, where two or more concepts are stuffed into a single data field (“Metadata Repositories,” TDWI Conference 1995). He described and portrayed in graphics three types of overloaded data. Almost 20 years later, overloaded data…