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.