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:
- It supports the principles of ‘layers’
- As we move down the layers, everything grows – the number of models, their complexity, and the number of objects included
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:
- Support for required levels and types of data models
- Generating new models from existing models
- Model subsets and model validation
- Definition of atomic data elements, prior to their incorporation in data models
- In Physical Data Models, direct support for all technology-specific object types
- Automated support for denormalization and common modeling tasks
- Managing the dependencies between models and between model objects
- Managed re-use of models and model objects, including model patterns
- Business vocabulary definition, mapped to usage within models
- Control over windows, toolbars, menus
- Diagram auto-layout, and control over symbol placement on diagrams
- Flexible editing and printing capabilities
- Object search
- Diagram image export
- Grouping related models as projects or configurations
- Expert, timely support
Interfaces and Integration
- Import and export data models
- Round-trip engineering
- Create or update a model based upon information held in spreadsheets
- Compare two data models of the same or different types, and update one or both models as a result (this may also be referred to as merging models)
- Generate test data to populate a test database or XML document
- Build cross-references or traceability links between data model objects and objects defined in other types of models, such as business process or enterprise architecture models, Business Requirement models, and Business Rules
- Provide comprehensive impact analysis by allowing users to interrogate the cross-references and traceability links in any way they choose
Management and Communication
- Extend the tool’s underlying data model, allowing analysts to change the way in which model objects are defined and to define new types of model objects
- Extract information from model objects for publication in various formats, such as html and documents
- Provide access to the content of models via a programmable interface, to provide a mechanism for the automation of repetitive tasks, and to extend the functionality provided by the tool
- Integrate with LDAP/Active Directory for user authentication
- A shared location for the storage of and controlled access to data models
- Provide direct access to models and links between models via a portal designed for use by non-specialist users of data models
- Resolve potentially conflicting changes made by different analysts
- Share reference models and common business rules via a repository
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