What are ADRM Software industry data models?

ADRM Software develops industry data models, which consist of a set of 21-30 industry-specific data models that reflect the information typically required by companies in a specific industry.

These models are developed from core competencies, direct industry experience, research and industry best-practices.

Each set of industry models consists of an Enterprise Data Model or a Data Warehouse Model and approximately 21-30 Business Area Models.

Each data model:

  • Is developed specifically for that industry
  • Has complete, business-friendly, industry-specific definitions and terms
  • Is developed using the erwin Data Modeler
  • Presented as a single-page, large-format, presentation quality plotted diagram

What industries are supported?

For a complete list of industries supported please refer to the Industry Models menu above or see the second page of the Data Model Datasheet which can be downloaded from the Downloads menu above.

What is a data model?

A data model is a graphic representation of the data within a specific area of interest.

A data model is the standard and accepted way of presenting data, analyzing data, designing and implementing applications and databases.

Data models are developed using CASE tools. CASE tools provide the supporting software for development of the data model including the graphics, data dictionary, links to other tools and supporting utilities.

The area of interest may be as broad as all the integrated data requirements of a complete business organization ("Enterprise Data Model") or as focused as a single business area or application ("Business Area Model").

Frequently a data model represents a business functional area (CUSTOMER, MARKETING, SALES, MANUFACTURING) or a business area that is to be analyzed or automated (LEAD TRACKING, PROBLEM REPORTING, WARRANTY).

A good data model depicts or describes the following:

  • Entities (tables)
  • Attributes (columns)
  • Relationships
  • Data cardinality
  • Business rules
  • Complete definitions of entities and attributes
  • Primary, secondary and alternate keys
  • Large-format, clear graphics

The goal of the data model is to clearly convey the meaning of data, the relationships amongst data, the attributes of the data and record the precise definitions of data.

The data model for a business organization tends not to change greatly over time unless the business changes the fundamental way that it does business or enters into a new line of business. However, the way that data is used, the processes, can vary greatly even between organizations functioning in the same industry.

The data required by organizations within the same industry tend to be very similar. This is why we can assume that data models have basic stability within the organization while process models are relatively unstable.

This common data is the basic principle that allows 'template' data models for an industry to be applied by organizations operating in that industry.

What is the Enterprise Data Model?

The Enterprise Data Model incorporates the integrated data requirements of a best-of-breed organization in that industry within a single model typically exceeding 400 entities and 2,500 attributes.

It is the essential data model for strategic planning, communicating information requirements across the organization, developing integrated systems and organizing data in the business area, data warehouse and data mart models.

Each Enterprise Data Model is built upon a common core of entity 'building blocks', which contributes those same common entities for construction of business area, data warehouse, data and application models.

This common set of core entities enables the related models to be data architected to be consistent and extendable. The same common core of entities are used wherever applicable in other industries, thus providing a means of integrating data across different industries or lines of business.

ADRM Software Enterprise Data Models have several common design characteristics:

  • Industry-specific design
  • Comprehensive subject area coverage
  • Fully-attributed
  • Complete and detailed definitions
  • Semantically clear and easy-to-understand
  • Reflects current industry data practices
  • Flexible and extendible design
  • Utilizes industry-standard data whenever possible
  • Large format graphic representation
  • Supports a wide audience of interests
  • Integrated with Business Area, DW and Data Mart models

Enterprise Data Models are physically presented as a single 36"x250" single-page, multicolor, plotted diagram.

The Enterprise Data Model is fully-attributes in third normal form (3NF) with complete definitions and documentation.

What is the Data Warehouse Model?

The data warehouse is the central repository for corporation information representing the integrated data requirements of the enterprise and designed to support the analysis, DSS and reporting requirements of the entire organization.

It has characteristics unique to its function:

  • Based upon a comprehensive enterprise data model
  • Provides integrated data to the organization
  • Serves a broad user community
  • Contains cleaned, consistent data
  • Data is at granular level of detail
  • Significant or often-used data is summarized
  • Contains time-based "historical" data
  • Driven by analytic requirements
  • Structured by aligned business areas
  • Addresses evolving information needs
  • Is not updated
  • Contains summary data

The Data Warehouse Model for each industry describes the target data structures and their data relationships in support of the enterprise-wide information requirements of a typical organization operating within that industry.

Each industry-specific Data Warehouse Model is derived directly from the same-industry Enterprise Data Model.

The Enterprise Data Model logical data structures are the foundation for development of corresponding data warehouse physical data structures.

What are Business Area Models?

Business Area Models describe functional business or subject areas found in many industries or developed for a specific industry.

Each Business Area Model is constructed from a common set of entities from the corresponding industry Enterprise Data Model, which insures that Business Area Models will have common keys, attributes and definitions throughout the data architecture.

Business Area Models expand upon the 'thumbnail' of business area data represented in the industry Enterprise Model and provide complete coverage for that subject area or business area.

Business Area Models contain the greatest level of detail and provide the lowest level of data granularity in the ADRM Software model hierarchy - while maintaining definitions consistent across the entire model suite.

This approach enables the organization to design top-down and propagate changes and new requirements consistently between models. As new information is added to a Business Area Model it can also be propagated to the Enterprise Model, Data Warehouse Model or Data Mart Model.

Business Area Models may be used in conjunction with the Enterprise Data Model to develop star schema data mart models. Having both the Enterprise Data Model and Business Area Models for reference facilitates consistent design and a resulting data architecture that implements conforming dimensions.

Business Area Models have the same components as the Enterprise Data Model and Data Warehouse Models:

  • Single-page, color, plotted diagrams
  • Detailed dictionaries
  • Complete definitions
  • Defined domains
  • ERwin Data Modeler CASE file

For a list of Business Area Models that are commonly used across multiple industries please refer to the Business Area Models menu above.

How are the data models integrated?

Each model is derived from the Enterprise Data Model for that industry. This supports the integration of data across each level of models.

The Enterprise Data Model becomes the source for creating new functional Business Area models and extending the Data Warehouse model.

Think of this as top-down engineering design with the Enterprise Data Model establishing the design at the top-level and Business Area Models adding scope, additional detail and complexity to that subject or area of interest.

New data, identified during business area development, that is considered to be of sufficient importance can be propagated up to the Enterprise Data Model.

This enhances the Enterprise Data Model and reflects new information learned about the enterprise during detailed business area analysis.

Similarly, the same analysis can contribute significant new data structures to the Data Warehouse Model and other Business Area Models.

CASE tools support the integration of data between models via utilities, subschemas and the central dictionary.

Who can take advantage of data models?

Almost everyone within the organization:

  • Data Architects and Analysts

    • Data architects and analysts now have a graphical and dictionary-based model that they can use to review software specifications, plan and develop new systems, integrate existing systems and jump-start projects.

    • Data models are valuable for determining the suitability of software packages and their application across an entire organization.

    • Data models also have components that are ideal for recording information about projects, applications, events and costs.

    • Data models can serve as vehicle for conveying this information across organizations and providing a source of continuity.

  • Senior Executives

    • Senior executives use data models to understand the integrated information data and associated responsibilities of the functional organizations within their responsibility.

    • Data models are powerful vehicles for understanding complex issues, communication and planning.

  • Managers

    • Managers use data models as tools for defining projects, assigning tasks, determining resources and prioritizing activities.

    • Data models are an excellent way for managers to describe their business responsibilities to others in terms of plans, objectives and goals.

  • Data Stewards

    • Data stewards use data and the associated business definitions and other metadata to ensure that all stakeholders can communicate clearly and precisely using the same terminology.

    • Data models which are part of an integrated set of industry-specific models can greatly assist in getting project requirements and scope correct early in a project while also highlighting any cross-functional dependencies or impacts.

  • Software Developers

    • Software developers need data to plan and build applications.

    • Industry models provide the base tables and relationships to prototype, compare against internal data structures and design new applications.

  • DBA's

    • DBA's use data models as the foundation for their designs, resource planning , backup strategies and security.

How can you design a data model for an industry?

Organizations within the same industry tend to perform the same basic functions, which require similar data.

The processes that work upon the data can vary considerably. However, the data, which is the foundation for current and future analysis and development, tends to remain stable unless the organization enters a new line of business or industry.

This makes it possible to create detailed, sophisticated 'template' data models that can be edited, extended and customized to meet organization-specific requirements.

This ability to edit, extend, customize and integrate each level of data model to meet the needs of a specific business organization is the key to the use of industry template data models.

ADRM Software industry data models make it is easy to work with each level of data models independently. This supports work-group development and facilitates rapid development of the data models as knowledge of each subject area is gathered.

It's also true that almost every company requires a core of similar functional components: Customers, Markets, Market Segments, Orders, Inventory, Pricing, Organization, Surveys, Standard Terms and Conditions, Pricing, Channels, Financial Accounts, BBB...

The use of template data models can dramatically improve the understanding of business areas and accelerate development of related systems.

The ability to move forward immediately without the lengthy period normally required to build baseline and industry data models is the tremendous advantage of template industry data models.

Template data models can be of value to almost any company.

How long would it take me to develop similar models?

Data models are very time-consuming to develop.

They are time-consuming because basic analysis must be performed such as the analysis of Order, Customer, Market, Channel and so on. This type of analysis could be obtained from 'template' models and edited to meet specific requirements.

An 'enterprise-wide' model can take one year or more to develop.

Subject area models typically take 3-6 months or more to complete and should be developed within the framework of the Enterprise Data Model to be consistent and integrated.

Data warehouse models require as much as one year or more to develop and should be developed within the context of the Enterprise Data Model with Business Area Models for reference. They should also integrate application and legacy data with physical data requirements.

It is normal for comprehensive modeling projects to cost millions of dollars.

Leveraging and editing industry data models is both more efficient and cost-effective than starting from scratch.

The advantages of buying template industry data models are:

  • Save time
  • Save money
  • Reduce staff
  • Avoid repetitive analysis
  • Knowledge transfer
  • See results immediately
  • Guaranteed quality and result

Planning is essential and expensive.

The way to shorten the process and reduce the costs is to purchase proven industry data models.

What services does ADRM Software provide?

ADRM Software and their business partners provide consulting services in support of industry data models:

  • Knowledge Transfer
  • IP Licensing/Applications
  • Strategic Planning
  • Business Subject Area Analysis
  • Client Mentoring
  • Data Resource Planning
  • Data Modeling
  • Data Warehouse Design
  • Data Warehouse Reviews
  • DSS Design and Development
  • EIS Development
  • Strategic Planning