Bitemporal Data Books

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Bitemporal Data


Bitemporal Data
  • Author : Tom Johnston
  • Publisher : Newnes
  • Release : 2014-08-19
  • ISBN : 9780124080553
  • Language : En, Es, Fr & De
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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. Explains the business value of bitemporal data in terms of the information that can be provided by bitemporal tables and not by any other form of temporal data, including history tables, version tables, snapshot tables, or slowly-changing dimensions. Provides an integrated account of the mathematics, logic, ontology and semantics of relational theory and relational databases, in terms of which current relational theory and practice can be seen as unnecessarily constrained to the management of nontemporal and incompletely temporal data. Explains how bitemporal tables can provide the time-variance and nonvolatility hitherto lacking in Inmon historical data warehouses. Explains how bitemporal dimensions can replace slowly-changing dimensions in Kimball star schemas, and why they should do so. Describes several extensions to the current theory and practice of bitemporal data, including the use of episodes, "whenever" temporal transactions and queries, and future transaction time. Points out a basic error in the ISO’s bitemporal SQL standard, and warns practitioners against the use of that faulty functionality. Recommends six extensions to the ISO standard which will increase the business value of bitemporal data. Points towards a tritemporal future for bitemporal data, in which an Aristotelian ontology and a speech-act semantics support the direct management of the statements inscribed in the rows of relational tables, and add the ability to track the provenance of database content to existing bitemporal databases. This book also provides the background needed to become a business ontologist, and explains why an IT data management person, deeply familiar with corporate databases, is best suited to play that role. Perhaps, in your organization, that person is you.

Exam Prep for Bitemporal Data Theory and Practice


Exam Prep for  Bitemporal Data  Theory and Practice
  • Author :
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  • Language : En, Es, Fr & De
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Data Warehousing and Knowledge Discovery


Data Warehousing and Knowledge Discovery
  • Author : Yahiko Kambayashi
  • Publisher : Springer Science & Business Media
  • Release : 2003-08-21
  • ISBN : 9783540408079
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2003, held in Prague, Czech Republic in September 2003. The 41 revised full papers presented were carefully reviewed and selected from more than 130 submissions. The papers are organized in topical sections on data cubes and queries, multidimensional data models, Web warehousing, change detection, Web mining and association rules, association rules and decision trees, clustering, association rule mining, data analysis and discovery, ontologies and improving data quality, queries and data patterns, improving database query engines, and sampling and vector classification.

Managing Time in Relational Databases


Managing Time in Relational Databases
  • Author : Tom Johnston
  • Publisher : Morgan Kaufmann
  • Release : 2010-08-19
  • ISBN : 0080963374
  • Language : En, Es, Fr & De
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Managing Time in Relational Databases: How to Design, Update and Query Temporal Data introduces basic concepts that will enable businesses to develop their own framework for managing temporal data. It discusses the management of uni-temporal and bi-temporal data in relational databases, so that they can be seamlessly accessed together with current data; the encapsulation of temporal data structures and processes; ways to implement temporal data management as an enterprise solution; and the internalization of pipeline datasets. The book is organized into three parts. Part 1 traces the history of temporal data management and presents a taxonomy of bi-temporal data management methods. Part 2 provides an introduction to Asserted Versioning, covering the origins of Asserted Versioning; core concepts of Asserted Versioning; the schema common to all asserted version tables, as well as the various diagrams and notations used in the rest of the book; and how the basic scenario works when the target of that activity is an asserted version table. Part 3 deals with designing, maintaining, and querying asserted version databases. It discusses the design of Asserted Versioning databases; temporal transactions; deferred assertions and other pipeline datasets; Allen relationships; and optimizing Asserted Versioning databases. Integrates an enterprise-wide viewpoint with a strong conceptual model of temporal data management allowing for realistic implementation of database application development. Provides a true practical guide to the different possible methods of time-oriented databases with techniques of using existing funtionality to solve real world problems within an enterprise data architecture environment. Written by IT professionals for IT professionals, this book employs a heavily example-driven approach which reinforces learning by showing the results of puting the techniques discussed into practice.

Very Large Data Bases


Very Large Data Bases
  • Author :
  • Publisher :
  • Release : 2001
  • ISBN : UOM:39015049127619
  • Language : En, Es, Fr & De
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