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Key Features Needed in a Data Modeling Tool
Published: January 1, 2012 Steve Hoberman and George McGeachie discuss the use of data modeling tools and point out the key features of those tools.
Tools are necessary for data modeling. You can't avoid having them, but which one suits you? Well, that depends on what you want to do with those tools, where you want to work in the Data Model Pyramid.
Many practitioners of data modeling use a pyramid to illustrate the different types of model that can be produced - this particular shape is well suited to the task for two reasons:
![]() The top two layers are occupied by subject area models, which show the key concepts in a particular area and how these concepts interact with each other. There are three types of subject area models: the Business Subject Area Model (BSAM), the Application Subject Area Model (ASAM), and the Comparison Subject Area Model (CSAM). A logical data model (LDM) takes the business need defined on a subject area model down to the next level of a business solution. A physical data model (PDM) takes the business solution defined on a logical data model to the next level of a technical solution. There are dependencies between the different types of data models shown in the pyramid, between data models and other artifacts or models that represent other aspects of business and requirements, the enterprise and solutions architecture, and application design. The activities required when producing and managing data models are only part of a wider set of business and technology activities; integration with associated activities is key to the success of data modeling. Without a tool that provides specialized support for data modeling, the data modeler cannot hope to work effectively in this environment. With data modeling tools, the wider your use of data models within the organization, the more features you tend to need. The key features you need in a tool can be categorized as follows: Core Modeling
Management and Communication
Collaboration
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Steve Hoberman -
Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modeling. He has worked as a business intelligence and data management practitioner and trainer since 1990. Steve is known for his entertaining, interactive teaching and lecture style (watch out for flying candy!) and is a popular, frequent presenter at industry conferences, both nationally and internationally. Steve is a columnist and frequent contributor to industry publications, as well as the author of Data Modeler’s Workbench and Data Modeling Made Simple. He is the founder of the Design Challenges group and inventor of the Data Model Scorecard™. Please visit his website www.stevehoberman.com to learn more about his training and consulting services, and to sign up for his Design Challenges! He can be reached at me@stevehoberman.com.
George McGeachie - George McGeachie has worked in the field of modeling and metadata in a variety of industries for many years. George has evaluated, implemented, tailored and used various data modeling
and metadata management tools during data modeling assignments around the
globe. He is joint author of Data Modeling Made Simple with PowerDesigner.
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