Tag: Business Analysis
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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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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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Data Management: So Easy a Caveman Can Do It?
I recently stumbled upon one of The Martin Agency’s hilarious Geico caveman ads and wondered, rather geekily, why they didn’t do one about data analysis. I think if a caveman suddenly arrived in the 2010s he or she would see parallels between his life and the activities of today’s knowledge worker. When I thought it through,…
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Selected data modeling best practices
Recently I was in a conversation about data modeling standards. I confess that I’m not really the standards type. I understand the value of standards and especially how important it is to follow them so others can interpret and use work products. It is just that I prefer to focus on understanding of the principles…
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Abstracting and recombining all the way to the bank
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…
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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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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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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…
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SQL Saturday #30, Richmond Virginia, April 10, 2010
Thanks to all who attended my presentations at SQL Saturday on April 10. Here are the materials from my two presentations: – The Business End of Data Modeling (2.5m powerpoint presentation) – Normalize Metadata For Data Integration Analysis (5.5m full version, zip including presentation and code samples) – Normalize Metadata For Data Integration Analysis (small)…