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Publications » Computers » Database Management

Joe Celko's Data & Databases

Price £37.99

temporarily out of stock

Joe Celko's Data & Databases

Joe Celko

ISBN 1558604324
Pages 448

Description

Do you need an introductory book on data and databases? If the book is by Joe Celko, the answer is yes. Data and Databases: Concepts in Practice is the first introduction to relational database technology written especially for practicing IT professionals. If you work mostly outside the database world, this book will ground you in the concepts and overall framework you must master if your data-intensive projects are to be successful. If you're already an experienced database programmer, administrator, analyst, or user, it will let you take a step back from your work and examine the founding principles on which you rely every day-helping you to work smarter, faster, and problem-free.

Whatever your field or level of expertise, Data and Databases offers you the depth and breadth of vision for which Celko is famous. No one knows the topic as well as he, and no one conveys this knowledge as clearly, as effectively-or as engagingly. Filled with absorbing war stories and no-holds-barred commentary, this is a book you'll pick up again and again, both for the information it holds and for the distinctive style that marks it as genuine Celko.

Contents
01.0 Preface 01.1 Organization of the Book 01.2 Corrections and Future Editions 02.0 The Nature of Data 02.1 Data versus Information 02.2 Information versus Wisdom 02.2.1 Innumeracy 02.2.2 Bad Math 02.2.3 Causation and Correlation 02.2.4 Testing the Model against Reality 02.3 Models versus Reality 02.3.1 Errors in Models 02.3.2 Assumptions about Reality 03.0 Entities, Attributes, Values and Relationships 03.1 Entities 03.1.1 Entities as Objects 03.1.2 Entities as Relationships 03.2 Attributes 03.3 Values 03.4 Relationships 03.5 ER Modeling 03.5.1 Mixed Models 03.6 FORM Modeling 04.0 Data Structures 04.1 Sets 04.2 Multi-sets 04.3 Simple Sequential Files 04.4 Lists 04.5 Arrays 04.6 Graphs 04.7 Trees 05.0 Relational Tables 05.1 Subsets 05.2 Union 05.3 Intersection 05.4 Set difference 05.5 Partitioning 05.5.1 Groups 05.5.2 Relational Division 05.6 Duplicates 05.6.1 Allow Duplicates 05.6.2 Disallow Duplicates 05.6.3 Consolidate Duplicates 05.6.4 Uniqueness 05.6.5 Levels of Aggregation 05.7 VIEWs 05.7.1 Updatable VIEWs 06.0 Access Structures 06.1 Indexes 06.1.1 Simple Indexes 06.2 Tree Structured Indexes 06.3 Covering Indexes 06.4 Hashing Functions 06.4.1 Uniform Hashing Function 06.4.2 Perfect Hashing Function 06.4.3 Minimal Hashing Functions 06.4.4 Multi-column Hashing Functions 06.5 Inverted Files 06.6 Bit Vector Indexes 06.7 Mixed Access Methods 06.8 Multiple Table Access Structures 06.9 An Informal Survey of Database Products 07.0 Numeric Data 07.1 Tag Numbers or Absolute Scales 07.2 Cardinal Numbers 07.3 Ordinal Numbers 07.3.1 Arithmetic with Ordinals, Cardinals and Tags 07.4.0 Computer Representations 07.4.1 Exact Numeric Representations 07.4.2 Approximate Numeric Representations versus the Continuum 07.5 Zero, NULL and Math 07.5.1 Zero, NULL and Division 07.5.2 Zero and Powers 07.6 Rounding and Truncating 07.6.1 Applied To Individual Values 07.6.2 Applied To Sets of Values 07.7 Addition and Summation are Different 07.8 Exotic Numbers 07.8.1 Fractions 07.8.2 Repeating Decimals 07.8.3 Infinite Precision Numbers 07.8.4 Complex Numbers 07.8.5 Coordinates 08.0 Character String Data 08.1 National Character Sets 08.2 Problems of String Equality 08.2.2 Empty String versus NULL String 08.3 Length 08.4 Concatenation 08.5 Position 08.6 Reversal 08.7 Pattern matching 08.8 Language as Data 08.8.1 Syntax versus Semantics 08.8.2 Computerized Language Translation 09.0 Logic and Databases 09.1 Boolean or Two Valued Logic 09.2 Multi-valued Logic 09.2.2 SQL-92 and Three Valued Logic 09.3 Fuzzy Sets, Logic and Math 09.3.1 Fuzzy Logic operators 09.3.2 Fuzzy Math Operators 09.4 Constructionist Logic 10.0 Temporal Data 10.1 Temporal Terminology 10.1.1 Events 10.1.2 Durations 10.1.3 Periods 10.1.4 Time in Databases 10.2 A Short History of the Calendar 10.3 The Julian Date 10.4 ISO Temporal Standards 10.4.1 ISO Date Formats 10.4.1.1 Calendar Date Format 10.4.1.2 Ordinal Date Format 10.4.1.3 Week Format 10.5 The Year 2000 Problem 10.5.1 The Odometer Problem 10.5.2 The Leap Year Problem 10.5.3 The Millennium Problem 10.5.4 Weird Dates 10.5.5 Solutions 10.6 ISO Time of Day 10.6.1 Local Time, lawful Time and UTC 10.7 Notes on SQL-92 and Temporal Data 10.7.1 Time Zones in SQL-92 10.7.2 the OVERLAPS Predicate 11.0 Textual Data 11.1 Terminology and the Basics 11.2. Indexing Text 11.3 Text Searching 11.4 The grep() Search Tool 11.5 ANSI and ISO Search Languages 11.5.1 ANSI Common Command Language 11.5.2 The ISO 8777 Language 12.0 Exotic Data 12.1 Nature of Data Manipulation 12.2 Physical versus Perceptual Data 12.2.1 Physical Data 12.2.2 Perceptual Data 12.3 Stored versus Constructed Data 12.4 SQL/MM 13.0 Missing data 13.1 Types of missing Data 13.1.1 Unknown 13.1.2 Not Applicable 13.1.3 Missing 13.1.4 Not Classified 13.1.5 Erroneous Data 13.1.5.1 Illegal Results 13.1.5.2 Error in Representation 13.1.5.3 Limited Values 13.2 The NULL in SQL 14.0 Scales and Measurements 14.1 Range and Granularity 14.1 Scales and Measurements 14.1.1. Range 14.1.2. Granularity and Precision 14.2 Types of Scales 14.3 Scale Conversion 14.4 Derived Units 14.5 Punctuation and Standard Units 14.6 General Guidelines for Using Scales in a Database 15.0 Data Encoding Schemes 15.1 Bad Encoding Schemes 15.1.2 Characteristics of a Bad Encoding Scheme 15.2 Encoding Scheme Types 15.2.1 Enumeration Encoding 15.2.2 Scale Encoding 15.2.3 Abbreviation Encoding 15.2.4 Algorithmic Encoding 15.2.5 Hierarchical Encoding 15.2.6 Vector Encoding 15.2.6.1 Social Security Numbers 15.2.7 Concatenation Encoding 15.3 General Guidelines for Designing Encoding Schemes 15.3.1 Existing Encoding Standards 15.3.2 Allow for Expansion 15.3.3 Use Explicit Missing Values To Avoid Nulls 15.3.4 Translate Codes for the User 15.3.5 Keep the Codes in the Database 16. Check Digits 16.1 Error Detection versus Error Correction 16.2 Mod Functions and Casting Functions 16.2.1 Mod Function 16.2.2 Casting Functions 16.3 Classes of Algorithms 16.3.1 Weighted-Sum Algorithms 16.3.2 Power-Sum Check Digits 16.3.3 Bull Check Digits 16.3.4 Dihedral Five Check Digit 16.4 Check Digit Algorithms 16.4.1 Casting Nines 16.4.2 Dihedral Five Check Digits 16.4.3 Bull Function 16.4.4 Power Function 16.4.5 SKU Code Algorithm 16.4.5 ISBN Function 16.4.6 Code 39 Algorithm 17.0 The Basic Relational Model 17.1 Tables versus Files 17.1.1 Tables as Entities 17.1.2 Tables as Relationships 17.2 Rows versus Records 17.3 Columns versus Fields 17.4 Relationships among Tables within a database 17.5 Codd's Rules for a Relational Database 18.0 Keys 18.1 Types of keys 18.2 Intelligent Keys versus Surrogate Keys. 18.2.1 Arguments against Intelligent Keys 18.2.1.1 Autoincremented Surrogate Keys 18.2.1.2 (MAX() + 1) Surrogate key generators 18.2.1.2 Random Number Surrogate keys 18.2.1.3 Surrogate Key Tables 18.2.2 Arguments for Intelligent Keys 18.2.2.1 Saving Space in the Database 18.2.2.2 Verification of the Data 18.2.2.3 Changing Surrogate Keys is Hard 18.2.2.4 Getting New Keys 18.2.2.5 Clustering Versus Random Distribution 18.2.2.6 Standards Versus Roll Your Own' 18.2.2.7 Data Warehousing 18.2.2.8 Replicated and Distributed Databases 18.3 Simple versus Compound Keys 18.3.1 Super keys and Overlapping Keys 18.3.2 Queries with Compound keys 19.0 Different Relational Models 19.1 Chris Date = no duplicates