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Relational Databases: Why So Many Tables?

Relational Databases: Why So Many Tables?. William Blozan, Ph.D. wblozan@fastanswers.com. Fast Answers. Introduction . Database Development: Programming, Data Theory & Business Management What is Relational Modeling? How Many Tables Do I Need, and Why so Many?

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Relational Databases: Why So Many Tables?

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  1. Relational Databases: Why So Many Tables? William Blozan, Ph.D. wblozan@fastanswers.com Fast Answers

  2. Introduction • Database Development: Programming, Data Theory & Business Management • What is Relational Modeling? • How Many Tables Do I Need, and Why so Many? • This Topic Is of Interest to All Levels of Database Developers.

  3. Agenda • Symptoms of Dysfunction • The Challenge • What’s at Stake • Key Design Concepts • Recommended Steps For Modeling Tables • Additional Modeling Complexity • Recommended Steps For Managing Tables • Managing Table Complexity in the GUI • Example • Plan Initial Data Conversion

  4. Symptoms of Dysfunction • Insufficient Number of Fields. • Multiple Entry of Data. • Awkward Or Impossible Data Access. • Frequent User Entry Errors & Variations. • High Maintenance Complexity • Very Slow System Performance • Unwieldy Change Management

  5. Vocabulary • Flat File: Spreadsheets and Word Processors.0 (& misused RDBMS’s) • Boyce-Codd Normalization: The Theory is only 25 yrs old! • Object Modeling: Conceptual Layer • Relational Modeling: Logical Layer • DBMS: Handles the Physical Layer • Entity-Relationship Diagrams

  6. The Challenge • Seek To Design A Safe Data Repository • Seek To Provide Easy Data Entry • Seek To Provide Flexible Data Retrieval • Must Allow for Repository Extensions • Must Anticipate Additional Uses & Users • Seek Tolerable System Performance

  7. What’s At Stake • Stable Production System • End User Direct Access • Disaster Recovery • Total Development Time & Effort • Data Conversion Complexity

  8. Key Design Concepts • Single Source Data Repository • Application Independence • Objects are Nouns; Processes are Verbs • Process Logs are Nouns • Let the Data Speak! • Claim: Correct Model => All Sensible Reports are Feasible • Must be able to describe an “Arbitrary Record” for each table

  9. Recommended Steps For Modeling Tables • Identify Primary Strategic Objects • Each Object Becomes a Table • Identify Multi-Valued Fields => Each repeating field can mean a Child Table • Identify M-M Relationships => Each requires a Third Association Table

  10. Recommended Steps For Modeling Tables, Con’t • Identify each Data Processing Step • Each process warrants at least one log table • Consider Lookup Tables and Value Lists • Consider Adding a System Table and an Audit Log • Consider other Application Meta Data • Multi-User Processes => Temporary Tables may be necessary to isolate processes

  11. Additional Modeling Complexity • Use Content-Void Primary Keys • 1-1 Table Relationships Still Require a Parent • Self Joins track genealogy • Partial RI For Optional Foreign Keys • Track Embedded Value Lists • Using Cascade Delete • Data Events => Use Triggers • Watch Out: Time Order of Occurrence

  12. Recommended Steps For Building Tables • Finalize the Entity-Relationship Data Model • Name Carefully: tblNounAdjVerbAdverb • Build the Tables and Relationships • Use AutoNumbers as Primary Keys • Add all data columns/fields • Define Data Types, Column Sizes, Default Values, Indexing, Validation, etc. • Add Audit Fields, Temporary Conversion Source Fields

  13. Manage Table Complexity In Screens And Code • Start with Bound MS Access Forms • Linked Tabs and Sub-Forms • Zoom To Edit M-M Parents • Bound, But Empty • Events: BU, AU, AI, On Current, Triggers • Unbound Views Of Many Tables

  14. Example: Business Cards • 1-7 Tables • 2 Key Objects: Firms & People • M-M Association: Employee w/ Job Title • Lookups: Phone Type, Address Type • Phones?, Addresses? • => One Screen Functionality Is Complex • Unbound Form, Drop-Downs, Tricky Navigation • Easy To Use => Lots Of Code

  15. Plan Initial Data Conversion • Map Old To New, New To Old • Spot Compacted Tables: Extract • Spot Compacted Fields: Extract • Check For Required Fields • Check For Consistent Spelling of LU’s • Prepare & Save Queries/Scripts • Trap Source Tables & Keys

  16. Conclusion • Get It Right From The Start • OK, Then Fix It As Soon As You See It • Name Things Appropriately • Data Model Diagrams Aid Communication With Clients and Colleagues • Suppress Complexity From Users • Art or Science? Both!

  17. Where to get more information • Nothwind Traders – Sort of! • MS Access & SQL Server User Groups • Establish quid pro quo relationships • MS Access has “Analyzer” wizards • ERwin, Infomodeler, Visual Modeler • Database Processing, Kroenke & Dolan, SRA. • Understanding Relational Databases, Fabian Pascal, Wiley. • Consultants.

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