Authors | |
Publisher | Morgan Kaufmann |
Year | |
Pages | 400 |
Version | paperback |
Language | English |
ISBN | 9780124080676 |
Categories | Programming & scripting languages: general |
Bitemporal data has always been important. But it was not until 2011 that the ISO released a SQL standard that supported it. Currently, among major DBMS vendors, Oracle, IBM and Teradata now provide at least some bitemporal functionality in their flagship products. But to use these products effectively, someone in your IT organization needs to know more than how to code bitemporal SQL statements. Perhaps, in your organization, that person is you.
To correctly interpret business requests for temporal data, to correctly specify requirements to your IT development staff, and to correctly design bitemporal databases and applications, someone in your enterprise needs a deep understanding of both the theory and the practice of managing bitemporal data. Someone also needs to understand what the future may bring in the way of additional temporal functionality, so their enterprise can plan for it. Perhaps, in your organization, that person is you.
This is the book that will show the do-it-yourself IT professional how to design and build bitemporal databases and how to write bitemporal transactions and queries, and will show those who will direct the use of vendor-provided bitemporal DBMSs exactly what is going on "under the covers" of that software.
Bitemporal Data: Theory and Practice
1. Basic Concepts.
Part I. Theory 2. Time and Temporal Terminology 3. The Relational Paradigm: Mathematics 4. The Relational Paradigm: Logic 5. The Relational Paradigm: Ontology 6. The Relational Paradigm: Semantics 7. The Allen Relationships 8. Temporal Integrity Concepts 9. Temporal Entity Integrity 10. Temporal Referential Integrity
Part II. Practice 11. Temporal Transactions 12. Basic Temporal Queries 13. Advanced Temporal Queries 14. Future Assertion Time 15. Temporal Requirements 16. Bitemporal Data and the Inmon Data Warehouse 17. Semantic Integration via Messaging 18. Bitemporal Data and the Kimball Data Warehouse 19. The Future of Relational Databases