Tag: Data Modeling
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One More Species of Overloaded Data
A while back I wrote the post A Field Guide to Overloaded Data, which publicized the work of Duane Hufford, who examined different types of overloaded data during the 1990s. Over the years his classifications of overloaded data effectively categorized data anomalies I encountered in the wild. That is until recently, when a colleague encountered…
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Reengineered Processes Need Business-Defined Data
“Business process reengineering is the act of recreating a core business process with the goal of improving product output, quality, or reducing costs.”* Recently I’ve perused articles on business process reengineering and have been surprised to find that they share a lack of emphasis on data definition. By establishing a shared business vocabulary, identifying and…
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Data Architecture for Improved Dashboard Performance
Sometimes success seems like a data analytics team’s worst enemy. A few successful visualizations packaged up into a dashboard by a small skunkworks team can generate interest such that a year later the team has published scores of mission critical dashboards. As their use spreads throughout the organization, and as features expand to meet the…
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Meaningful Requirements Start Successful Data Projects
To me, development projects fail or succeed in the first few weeks. Once a project starts off in the wrong direction, momentum and expectations tend to prevent a return to the proper path. With today’s wealth of database options each addressing exciting new possibilities, the right choice for the application’s data foundation plays a large…
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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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Manage DATA, People, Process, and Technology
A quick Google search seems to reveal if you manage People, Process, and Technology you’ve got everything covered. That’s simply not the case. Data is separate and distinct from the things it describes — namely people, processes, and technologies — and organizations must separately and intentionally manage it. The data management message seems a tough…
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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…