Conceptual data modeling and database design : a fully algorithmic approach.: a fully algorithmic approach. The shortest advisable path / Volume 1, (2015)

• Record Type: Book
• Further Information: Note: Christian Mancas.
• Authors: Mancas, Christian
• Contents: Foreword by Professor Bernhard Thalheim Foreword by Professor Dan Suciu Preface Data, Information and Knowledge in the Computer Era Data, information, knowledge Data analysis and conceptual modeling Data and knowledge bases Constraints (business rules) Data and knowledge base management systems (DBMS, KBMS) Static and dynamic aspects of databases The Quest for Data Adequacy and Simplicity: The Entity-Relationship Data Model (E-RDM) Entity and relationship type object sets Attributes and surrogate keys Entity-Relationship Diagrams (E-RDs) Functional relationships and the Key Propagation Principle (KPP ) Relationship hierarchies Higher arity non-functional relationships Restriction sets Case study: a public library (do we know exactly what a book is?) The algorithm for assisting the data analysis and modeling process (A 0). An E-R data model of the E-RDM Best practice rules The math behind E-RDs and restriction sets. The danger of "many-to-many relationships" and the correct E-RD of E-RDM The Quest for Data Independence, Minimal Plausibility, and Formalization: The Relational Data Model (RDM ) First normal form tables, columns, constraints, rows, instances The five basic relational constraint types The algorithm for translating E-R data models into relational schemas and non-relational constraint sets (A 1-7). An RDM model of the E-RDM Case study: the relational scheme of the public library data model The reverse engineering algorithm for translating relational schemas into E-R data models (REA 1-2) The algorithm for assisting keys discovery (A 7/8-3) RDBMS metacatalogs. Relational and E-R data models of the RDM Relational schemas definition. SQL DDL Relational instances manipulation. SQL DML . Relational calculi and algebra Higher and the highest RDM normal forms Best practice rules The math behind RDM Relational Schemas Implementation and Reverse Engineering The algorithm for translating relational schemas into SQL DDL ANSI-92 scripts (A 8) Relevant differences between IBM DB2, Oracle Database and MySQL, Microsoft SQL Server and Access Case study: implementing the public library RDB into DB2, Oracle, MySQL, SQL Server, and Access The reverse engineering algorithm for translating Access 2013 RDB schemas into SQL ANSI DDL scripts (REA2013A 0), a member of REAF 0’ The algorithms for translating E-R data models into RDBs and associated non-relational constraint sets (AF 1-8) The reverse engineering family of algorithms for translating RDB schemas into E-R data models (REAF 0-2) Case study: reverse engineering of an Access Stocks DB scheme into both an ANSI standard SQL DDL script and an E-R data model Best practice rules The math behind the algorithms presented in this chapter Conclusion Database axioms Why do we need another conceptual level for expert DB design? What are the most important things that we should be aware of in DBs? Appendix: Mathematic prerequisites for the math behind Index
• Edition: 1st
• Publisher Details: Toronto : Apple Academic Press
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 005.743; Database design
• Languages: English
• ISBNs: 9781498728447
• Related ISBNs: 9781771881241
• Notes: Note: Description based on CIP data; item not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.