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Database Models: Flat Files and the Relational Database

Database Models: Flat Files and the Relational Database. Objectives : Understand the fundamental structure of the relational database model Learn the circumstances under which it is a better choice than the flat file. What is a database?. Structured Data Procedures for Data entry Storage

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Database Models: Flat Files and the Relational Database

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  1. Database Models: Flat Files and the Relational Database Objectives: Understand the fundamental structure of the relational database model Learn the circumstances under which it is a better choice than the flat file

  2. What is a database? • Structured Data • Procedures for • Data entry • Storage • Validity checking • Sorting • Selection • Reporting

  3. Why use a database? • To organize & preserve data • To facilitate analysis and modeling • To gain insights into the relationships in your data • To help turn data into information • To explore data using exploratory techniques • To support the organization

  4. Flat file databases • Text files (word processing packages) • Loosely structured storage • Sorting (whole tables or individual columns, by number/data/text) • Reports (via mail and merging functions)

  5. Excel as a database • All Word database capabilities plus • Data entry • Selection/Queries • Statistics • Calculations • Graphics / chart development data summarization

  6. Relational Database Systems • All the features support by Excel • Plus all of the following features • Validity Checking • Relational queries • Extensive import/export capabilities • Object-oriented model • Strong data typing: support for formatted text, memo fields, OLE, calculated fields

  7. Why use the relational model? • Minimize redundancy • Minimize wasted storage • Facilitate updates, appending new data to existing systems • Facilitate queries, makes asking questions of the database easier • Keeps tables small for portability and improved data processing

  8. Things to be cautious about • Issues and Design considerations • Boolean, Integer, Long, Currency, Single, Double, Date, String, and Variant • How expressions with different data types are defined • When to split entries between different fields and when to combine them in a common field • When to use more than one table in a data base and when to use only one table

  9. Other things to consider • Redundancy – unnecessary repetition of information, wastes computing resources • One-to-one relationships • One-to-many relationships • Many-to-many relationships (special case)

  10. Databases are dynamic • Can accept entry of new data even while displaying results from current data • Desktop vs. Client/Server • Transaction databases • Internet databases

  11. Timber Stand Inventory Information in each column are the attributes of the database, information in each row are records.

  12. How to design a relational database • Identify the purpose of the relational database • Identify the various the subjects of the database • Determine what information on each subject is necessary • Determine how the subject information is related to other subject information • Refine and redesign the database when design flaws are identified. Final designs are seldom the first designs considered.

  13. Example • Tall Timbers Forest Management Inc. • Tables • Forest communities • Harvest schedules • Prescribed burn schedule • Wildlife habitat quality • Riparian management objectives • Restoration plans • Special concerns for threatened and endangered species

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