Home > Ask the Data Management Experts > Data architecture / Data modeling Questions & Answers > Data model conversion: Conceptual design to logical design using an ER model
Ask The Data Management Expert: Questions & Answers
EMAIL THIS

Data model conversion: Conceptual design to logical design using an ER model

Pete Stiglich EXPERT RESPONSE FROM: Pete Stiglich

Pose a Question
Other Data Management Categories
Meet all Data Management Experts
Become an Expert for this site


Tips, expert advice and sample chapters
Digg This!    StumbleUpon Toolbar StumbleUpon    Bookmark with Delicious Del.icio.us    Add to Google


>
QUESTION POSED ON: 21 April 2008
Can you give me a scenario converting a data model from conceptual design to logical design by using entity-relationship (ER)?

>
EXPERT RESPONSE
Depending upon your tool and modeling notation, your Conceptual Data Model (CDM) may already be an entity-relationship (ER) model. CDMs should, in most cases, be business models -- and not data design models (as is the Logical Data Model (LDM)), so your CDM should identify real world business objects (e.g. Customer, Order, Sale, Policy, etc) and the relationships between these. In other words, CDM's are not design -- they are used to describe the business. Data design comes into play in the LDM.

There are different schools of thought regarding converting your CDM to LDM. The traditional and most common approach entails:

  • Identifying all applicable entities (CDM doesn't express all the details)
  • Fully/mostly attributizing data entities (with business nomenclature)
  • Assigning datatype domains (e.g. text, date, numeric) vs. datatypes (varchar, integer)
  • Resolving M:M relationships (e.g. with an associative entity, record versioning, etc)
  • Formalizing keys (primary, alternate, foreign)
  • Resolutions of subtypes (3 methods for resolution)
  • Performing abstraction (e.g. abstracting conceptual entities such as Customer, Prospect, Supplier, etc. into a generalized entity such as Party) as part of the normalization process (so that data can be stored once)

This approach follows the definition of the LDM as "provable by the mathematics of data science." (Applied Information Science website)

Another approach is to make the LDM largely an attributized CDM, with the resolutions above taking place in the Physical Data Model. The advantage is that a single LDM could have many physical manifestations, e.g. for a normalized online transaction processing (OLTP) application or as a denormalized dimensional data mart, and the meta data relationships are automatically maintained. This approach is more appropriate for enterprise models as there can be a wide degree of applicable situations where the entity may be required.

The downside is that complexity is increased, clarity may be decreased, and in many shops a first-cut PDM is created by the Data Architect/Modeler and handed off to the DBA for further changes for performance and maintainability (with the review and approval of the DA/Modeler!). When this occurs the LDM and PDM might be maintained in separate files -- thus minimizing the data lineage benefits.

More about conceptual data models

  • Four guidelines for enterprise conceptual data model (ECDM) entity selection
  • What are the benefits of a conceptual data model?
  • A guide to conceptual data models for IT managers
  • More about logical data models

  • Logical data models and normalization

  • Digg This!    StumbleUpon Toolbar StumbleUpon    Bookmark with Delicious Del.icio.us    Add to Google


    RELATED CONTENT
    Data architecture / Data modeling
    Data architect vs. application architect: Segregate the duties
    Enterprise versus project level conceptual data modeling
    XML schema definition versus conceptual data model
    Four guidelines for enterprise conceptual data model (ECDM) entity selection
    Data modeling for data warehouse projects
    Data architecture vs. information architecture
    What are the benefits of a conceptual data model?

    Data modeling
    Data architect vs. application architect: Segregate the duties
    Enterprise versus project level conceptual data modeling
    XML schema definition versus conceptual data model
    Four guidelines for enterprise conceptual data model (ECDM) entity selection
    Building a business case for data modeling
    Data modeling for data warehouse projects
    Embarcadero unveils support for Universal Data Models
    What are the benefits of a conceptual data model?
    Definitions of design and data modeling
    What is a data model?

    RELATED GLOSSARY TERMS
    Terms from Whatis.com − the technology online dictionary
    data modeling  (SearchDataManagement.com)
    predictive modeling  (SearchDataManagement.com)

    RELATED RESOURCES
    2020software.com, trial software downloads for accounting software, ERP software, CRM software and business software systems
    Search Bitpipe.com for the latest white papers and business webcasts
    Whatis.com, the online computer dictionary



    Search and Browse the Expert Answer Center
    Search and browse more than 25,000 question and answer pairs from more than 250 TechTarget industry experts.
    Browse our Expert Advice

    About Us  |  Contact Us  |  For Advertisers  |  For Business Partners  |  Site Index  |  RSS
    SEARCH 
    TechTarget provides enterprise IT professionals with the information they need to perform their jobs - from developing strategy, to making cost-effective IT purchase decisions and managing their organizations' IT projects - with its network of technology-specific Web sites, events and magazines.

    TechTarget Corporate Web Site  |  Media Kits  |  Reprints  |  Site Map




    All Rights Reserved, Copyright 2005 - 2008, TechTarget | Read our Privacy Policy
      TechTarget - The IT Media ROI Experts