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NoSQL & SQL Data Modeling: Bringing Together Data, Semantics & Software [Pehme köide]

  • Formaat: Paperback / softback, 260 pages, kõrgus x laius: 235x190 mm, kaal: 502 g
  • Ilmumisaeg: 01-Apr-2016
  • Kirjastus: Technics Publications LLC
  • ISBN-10: 1634621093
  • ISBN-13: 9781634621090
Teised raamatud teemal:
  • Formaat: Paperback / softback, 260 pages, kõrgus x laius: 235x190 mm, kaal: 502 g
  • Ilmumisaeg: 01-Apr-2016
  • Kirjastus: Technics Publications LLC
  • ISBN-10: 1634621093
  • ISBN-13: 9781634621090
Teised raamatud teemal:
Learn how to design a database for non-traditional NoSQL data strutures

The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases.This book will teach you: • the simple and familiar graphical notation of COMN with its three basic shapes and four line styles • how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren’t tangled with confused techno-speak • how to express logical data designs that are freer from implementation considerations than is possible in any other notation • how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms • how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development
Acknowledgements xiii
Introduction 1(16)
Taking Care of Data
3(2)
Plant Change Control 2.0
5(1)
Where did the Savings Come From?
5(3)
Why Model?
8(3)
Why COMN?
11(1)
Book Outline
12(1)
Book Audience
13(4)
NoSQL Database Developer
13(1)
SQL Database Developer
14(1)
Data Modeler
14(1)
Software Developer
14(1)
Ontologist
15(2)
Part I: Real Words in the Real World 17(26)
Chapter 1 It's All about the Words
19(4)
References
21(2)
Chapter 2 Things: Entities, Objects, and Concepts
23(6)
Glossary
28(1)
Chapter 3 Containment and Composition
29(6)
Containment
29(2)
Composition
31(2)
Glossary
33(2)
Chapter 4 Types and Classes in the Real World
35(8)
Collections of Objects
35(2)
Sets of Concepts
37(1)
Sets of Objects
38(1)
Types and Classes
38(3)
Types Designate Sets
39(1)
Classes Describe Objects
40(1)
Three Aspects of Types and Classes
41(1)
Glossary
41(2)
Part II: The Tyranny of Confusion 43(44)
Chapter 5 Entity-Relationship Modeling
45(14)
Logical E-R Data Models
45(3)
Multiple Levels of Abstraction
48(2)
Limitations of E-R Modeling Notation
50(6)
NoSQL Arrays and Nested Data Structures
50(1)
Lack of Reusable Composite Types
51(3)
Lack of Place
54(1)
Modeling the Real World
54(1)
Representing Individual Entities
55(1)
Mapping Between Models
55(1)
Data in Software
56(1)
Terminology
56(2)
Entity
56(1)
Conceptual
57(1)
E-R Terms Mapped to COMN Terms
57(1)
References
58(1)
Chapter 6 The Unified Modeling Language
59(8)
Class Diagrams
59(2)
Stereotyping
60(1)
Limitations of the UML
61(2)
Lack of Keys
61(1)
Middling Level of Abstraction
61(1)
Lack of Concept
62(1)
Subclassing versus Subtyping
62(1)
Terminology
63(2)
Relationship, Composition and Aggregation
63(1)
Type and Implementation Class
64(1)
UML Terms Mapped to COMN Terms
64(1)
References
65(2)
Chapter 7 Fact-Based Modeling Notations
67(8)
Facts and Relationships
67(2)
Limitations of Fact-Based Modeling
69(2)
Lack of Instances
70(1)
Incompleteness
70(1)
Difficulty
71(1)
Terminology
71(3)
Fact-Based Modeling Terms Mapped to COMN Terms
72(2)
References
74(1)
Chapter 8 Semantic Notations
75(8)
Predicates and RDF Statements
75(4)
Doubles and Quadruples
78(1)
OWL
79(1)
Graphical Notations for Semantics
80(1)
Terminology
80(3)
Chapter 9 Object-Oriented Programming Languages
83(4)
Classes, Objects, Types, and Variables
83(2)
Terminology
85(2)
Part III: Freedom in Meaning 87(126)
Chapter 10 Objects and Classes
89(16)
Material Objects
90(7)
Objects with States
90(1)
Meaning of States
91(1)
Objects with More States
92(2)
Even More States
93(1)
Methods
94(1)
Material Objects in Computers
94(2)
Summary
96(1)
Computer Object Defined
97(5)
Composing Objects
98(7)
Software Object Composition
98(3)
Authorizing Certain Routines
101(1)
Summary
102(2)
Glossary
104(1)
Chapter 11 Types in Data and Software
105(12)
Types in Programming and Databases
105(2)
What does a Type tell us?
106(1)
Classes in Object-Oriented Software
107(1)
Separating Type and Class
108(4)
Simple Types
112(4)
References
116(1)
Glossary
116(1)
Chapter 12 Composite Types
117(20)
Composite Types as Logical Record Types
117(2)
Types Representing Things in the Real World: Identification
119(4)
Stepwise Refinement and Completeness
122(1)
Types Representing Other Types
123(2)
Measures as Composite Types
125(3)
Nested Types
128(2)
Modeling Documents
130(2)
Arrays
132(3)
Glossary
135(1)
References
135(2)
Chapter 13 Subtypes and Subclasses
137(18)
Subtypes
137(7)
Restriction is Subtyping
143(1)
Subclasses
144(2)
Subtypes and Extensions: Perfect Together
146(5)
Inheritance
151(2)
Using Subtype Variables and Values
151(1)
Using Extending Types and Classes
152(1)
Projection: The Inverse of Extension
153(1)
Glossary
154(1)
Chapter 14 Data and Information
155(12)
Information
155(2)
Is Information Always True?
157(1)
From Information to Data
157(4)
Data en Masse
159(1)
Variable Names
160(1)
Summary
160(1)
Information and Data as Colloquialisms
161(4)
Information En Masse
161(1)
It's Just Data
161(1)
Putting it all Together
162(1)
"Unstructured Data" and "Semi-Structured Data"
163(2)
Data Object
165(1)
Glossary
166(1)
Chapter 15 Relationships and Roles
167(10)
Arrivals and Departures
167(3)
Labeling Relationship Lines
170(4)
Cleaning up the Model
171(3)
Roles, Predicates, and Relationships
174(1)
Glossary
175(2)
Chapter 16 The Relational Theory of Data
177(20)
What is a Relation?
178(4)
The Order of Rows
178(2)
The Uniqueness of Rows
180(1)
The Significance of Columns
181(1)
Summary
182(1)
Technical Relational Terminology
182(5)
Tuple and Relation Schemes
185(1)
Giving Data to the System
185(1)
Data Attribute Versus Attribute
186(1)
Relational Terminology Reprise
187(1)
Composite Data Attributes
187(3)
Relational Operations
190(1)
NoSQL Versus the Relational Model
191(1)
SQL Versus the Relational Model
192(1)
Terminology
193(1)
Glossary
194(3)
Chapter 17 NoSQL and SQL Physical Design
197(16)
What's Different about NoSQL?
197(1)
Database Performance
198(1)
ACID versus BASE and Scalability
199(4)
ACID
199(2)
Atomicity
200(1)
Consistency
200(1)
Isolation
200(1)
Durability
201(1)
BASE and CAP
201(2)
NoSQL and SQL Data Organization
203(8)
Key/Value DBMS
204(1)
Graph DBMS
205(1)
Document DBMS
206(1)
Columnar DBMS
207(1)
Tabular DBMS
208(3)
Summary
211(1)
References
211(2)
Part IV: Case Study 213(18)
Chapter 18 The Common Coffee Shop
215(16)
Analysis: Documenting Real-World Entities
215(5)
Logical Data Modeling: Designing the Data
220(6)
Physical Data Modeling: Designing the Implementation
226(5)
Appendix: COMN Quick Reference 231(4)
Glossary 235(4)
Photo and Illustration Credits 239(2)
Index 241