...INTERNATIONAL UNIVERSITY A Model Theory for Generic Schema Management Models Kinan M Al Haffar UM4699SIT10550D 07/08/2007 Abstract The core of a model theory for generic schema management is developed. This theory has two distinctive features: it applies to a variety of categories of schemas, and it applies to transformations of both the schema structure and its integrity constraints. A subtle problem of schema integration is considered in its general form, not bound to any particular category of schemas. The proposed solution, as well as the overall theory, is based entirely on schema morphisms that carry both structural and semantic properties. Duality results that apply to the two levels (i.e., the schema and the data levels) are established. These results lead to the main contribution of this paper: a formal schema and data management framework for generic schema management. Implications of this theory are established that apply to integrity problems in schema integration. The theory is illustrated by a particular category of schemas with object-oriented features along with typical database integrity constraints. 1 Introduction This paper presents the core results of a model theory for generic schema management, by which we mean schema and database transformation capabilities that are independent of a particular data model. Such transformations require major database programming tasks, such as integrating source schemas when building a data warehouse or integrating...
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... evaluate the significance of the Entity-Relationship Model (ER model) for DB design, enumerate the basic constructs of the ER model, develop ER diagrams (schemas in the ER model) for a given application, translate ER models into equivalent (as far as possible) relational models. Marc H. Scholl (DBIS, Uni KN) Information Management Winter 2007/08 48 2. The Entity-Relationship Model Introduction Database design (1) Overall goal of DBMS usage: Efficiently develop programs to support given real-world tasks. These programs need to store data persistently. To develop these programs, apply proven methods of software engineering—specialized to support data-intensive programs. Definition (Database Design) Database Design is the process of developing a database schema for a given application. DB design is a subtask of the overall software engineering effort. Marc H. Scholl (DBIS, Uni KN) Information Management Winter 2007/08 49 2. The Entity-Relationship Model Introduction Database design (2) The specification of programs and data is intertwined: The schema should contain the data needed by the programs. Programs are often easy to develop once the structure of the data to be manipulated has been specified. Data, however, is an independent resource: Typically, additional programs will be developed later based on the collected data. Also, ad-hoc queries will be posed against the DB. Marc H. Scholl (DBIS, Uni KN) Information Management Winter 2007/08 ...
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...Review of Major DB Concepts • Data and Information – Data: raw facts – Information: processed data • • • • Database Metadata DBMS: Database management system Database system 1 An Example of Data • Sales per employee for each of Xcompany’s two divisions 2 Data and Its Structure • Data is actually stored as bits, but it is difficult to work with data at this level. • It is convenient to view data at different levels of abstraction. • Schema: Description of data at some level. Each level has its own schema. • Three schemas: physical, conceptual, and external. 3 Physical Data Schema • Describes details of how data is stored: tracks, cylinders, indices etc. • Early applications worked at this level - explicitly dealt with details. • Problem: Routines hard-coded to deal with physical representation. – Changes to data structure difficult to make. – Application code becomes complex since it must deal with details. – Rapid implementation of new features impossible. 4 Conceptual Data Level • Hides details. – In the relational model, the conceptual schema presents data as a set of tables. • DBMS maps from conceptual to physical schema automatically. • Physical schema can be changed without changing application: – DBMS must change mapping from conceptual to physical. • Referred to as physical data independence. 5 Conceptual Data Level (con’t) Application Conceptual view of data DBMS Physical view of data 6 External Data Level ...
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...1.Introduction Relational database design theory is mainly based on a class of constraints called Functional Dependencies (FDs).FDs are a generalization of keys. This theory defines when a relation is in normal form (e.g., in Third Normal Form or 3NF) for a given set of FDs. It is usually a sign of bad DB design if a schema contains relations that violate the normal form requirements. If a normal form is violated, data is stored redundantly, and information about different concepts is intermixed. To reduce the redundancy in a given relation we need to decompose it in two or more sub relations . Decomposition into highest normal forms required maintaining properties like loss less join decomposition and dependency preserving decomposition. To normalize a relation R we have to remove certain dependencies that exist in it like partial dependency& transitive dependency. Basic definitions 1.1 Functional dependency: In a given table, an attribute Y is said to have a functional dependency on a set of attributes X (written X → Y) if and only if each X value is associated with precisely one Y value. For example, in an "Employee" table that includes the attributes "Employee ID" and "Employee Date of Birth", the functional dependency {Employee ID} → {Employee Date of Birth} would hold. It follows from the previous two sentences that each {Employee ID} is associated with precisely one {Employee Date of Birth}. 1.2 Trivial functional dependency A trivial functional dependency...
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...• Relational Model Constraints and Relational Database Schemas • Update Operations, Transactions, and Dealing with Constraint Violations 2 The Relational Data Model and Relational Database Constraints • Relational model – First commercial implementations available in early 1980s – Has been implemented in a large number of commercial systems • Hierarchical and network models – Preceded the relational model 3 Relational Model Concepts • Represents data as a collection of relations • Table of values – Row • Represents a collection of related data values • Fact that typically corresponds to a real-world entity or relationship • Tuple – Table name and column names • Interpret the meaning of the values in each row attribute 4 Relational Model Concepts (contd) 5 Domains, Attributes, Tuples, and Relations • Domain D – Set of atomic values • Atomic – Each value indivisible • Specifying a domain – Data type specified for each domain 6 Domains, Attributes, Tuples, and Relations (contd) • Relation schema R – Denoted by R(A1, A2, ...,An) – Made up of a relation name R and a list of attributes, A1, A2, ..., An • Attribute Ai – Name of a role played by some domain D in the relation schema R • Degree (or arity) of a relation – Number of attributes n of its relation schema 7 Domains, Attributes, Tuples, and Relations (contd) • Relation (or relation state) – Set of n-tuples r = {t1, t2, ..., tm} – Each n-tuple...
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...Contents Preface 1 Chapter 1 Introduction Exercises 4 Chapter 2 Entity Relationship Model Exercises 9 Chapter 3 Relational Model Exercises 30 Chapter 4 SQL Exercises 42 Chapter 5 Other Relational Languages Exercises 58 Chapter 6 Integrity and Security Exercises 74 iii iv Contents Chapter 7 Relational-Database Design Exercises 84 Chapter 8 Object-Oriented Databases Exercises 98 Chapter 9 Object-Relational Databases Exercises 109 Chapter 10 XML Exercises 119 Chapter 11 Storage and File Structure Exercises 129 Chapter 12 Indexing and Hashing Exercises 141 Chapter 13 Query Processing Exercises 155 Chapter 14 Query Optimization Exercises 166 Chapter 15 Transactions Exercises 175 Chapter 16 Concurrency Control Exercises 182 Chapter 17 Recovery System Exercises 194 Contents v Chapter 18 Database System Architectures Exercises 201 Chapter 19 Distributed Databases Exercises 208 Chapter 20 Parallel Databases Exercises 217 Chapter 21 Application Development and Administration Exercises 225 Chapter 22 Advanced Querying and Information Retrieval Exercises 232 Chapter 23 Advanced Data Types and New Applications Exercises 241 Chapter 24 Advanced Transaction Processing Exercises 249 C H A P T E R 1 Introduction Chapter 1 provides a general overview of the nature and purpose of database systems. The most important concept in...
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...Introduction to Data Warehousing and Business Intelligence Slides kindly borrowed from the course “Data Warehousing and Machine Learning” Aalborg University, Denmark Christian S. Jensen Torben Bach Pedersen Christian Thomsen {csj,tbp,chr}@cs.aau.dk Course Structure • Business intelligence Extract knowledge from large amounts of data collected in a modern enterprise Data warehousing, machine learning Acquire theoretical background in lectures and literature studies Obtain practical experience on (industrial) tools in practical exercises Data warehousing: construction of a database with only data analysis purpose • Purpose Business Intelligence (BI) Machine learning: find patterns automatically in databases 2 •1 Literature • Multidimensional Databases and Data Warehousing, Christian S. Jensen, Torben Bach Pedersen, Christian Thomsen, Morgan & Claypool Publishers, 2010 • Data Warehouse Design: Modern Principles and Methodologies, Golfarelli and Rizzi, McGraw-Hill, 2009 • Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications, Elzbieta Malinowski, Esteban Zimányi, Springer, 2008 • The Data Warehouse Lifecycle Toolkit, Kimball et al., Wiley 1998 • The Data Warehouse Toolkit, 2nd Ed., Kimball and Ross, Wiley, 2002 3 Overview • • • • Why Business Intelligence? Data analysis problems Data Warehouse (DW) introduction DW topics Multidimensional modeling ETL Performance optimization 4 •2 What is Business Intelligence (BI)? • From...
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...Review Questions Chapter 1 1.3 Describe the approach taken to the handling of data in the early file-based systems. In the early file based system their all data was in written form, due to the lake of education, due to the in-familiarity with new techniques, lake of computer knowledge so all the data required would be stored in a file or files owned by the programs. Discuss the disadvantages of this approach. Different programs could be written in different languages, and would not be able to access another program's files. This would be true even for those programs written in the same language, because a program needs to know the file structure before it can access it. 1.4 Describe the main characteristics of the database approach and contrast it with the file-based approach. Focus is now on the data first, and then the applications. The structure of the data is now kept separate from the programs that operate on the data. This is held in the system catalog or data dictionary. Programs can now share data, which is no longer fragmented. There is also a reduction in redundancy, and achievement of program-data independence. 1.5 Describe the five components of the DBMS environment and discuss how they relate to each other. (1) Hardware: The computer system(s) that the DBMS and the application programs run on. This can range from a single PC, to a single mainframe, to a network of computers. (2) Software: The DBMS software and the application...
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...Briefly describe the evolution of database systems and the limitations of conventional file processing systems 3. Describe the three schema architecture for database and explain the difference between conceptual , external and physical schemas 4. Define the functions of a database administrator Keywords and Phrases LEARNER Database Database System Entities Conceptual Model Logical Model Physical Model Constraints Metadata Database Management System File System Indexing Introduction This module introduces the reader to the different concepts of databases. It also tackles a brief history how automated databases came into existence. A number of advantages is discussed why the evolution of database management system is very much appreciated by system developers nowadays. 2 What is a Database ? Let us try to get the answers from the different Database Management System book authors. Answer from Pratt/Adamski: o A Database (DB) is structure that can store information about: 1. multiple types of entities, 2. the attributes that describe those entities; and 3. the relationships among the entities Answer from Elmasri/Navathe: o A Database (DB) is collection of related data - with the following properties: 1. A DB is logically coherent and has some relevant meaning 2. A DB is designed, built and populated with data for a specific purpose 3. A DB represents some aspect of the real world. Answer from Kroenke: An integrated, self-describing collection of related data o o...
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...Product Features 2.3 User Classes and Characteristics 2.4 Operating Environment 2.5 Design and Implementation Constraints 2.6 Assumptions and Dependencies 3. System Features 4. External Interface Requirements 4.1 User Interfaces 4.2 Hardware Interfaces 4.3 Software Interfaces 4.4 Communications Interfaces 5. Other Nonfunctional Requirements 5.1 Performance Requirements 5.2 Safety Requirements 5.3 Security Requirements 5.4 Software Quality Attributes 1. INTRODUCTION 1.1 PURPOSE The purpose of this document is to provide the software requirement specification report for the airline database. 1.2 DOCUMENT CONVENTIONS |DB |Data base | |DDB |Distributed Data base | |ER |Entity relationship | 1.3 INTENDED AUDIENCE AND READING SUGGESTIONS This project is the college level project and is implementing under the guidance of college professors. This project is useful to everyone who travels in flights. 1.4 PROJECT SCOPE The purpose of the online system is to create convenient and easy-to-use online system for...
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...Consistent Query Answers in Inconsistent Databases Marcel0 Arenas Pontificia Universidad Cat6lica de Chile Escuela de Ingenieria Departamento de Ciencia de Computaci6n Casilla 306, Santiago 22, Chile marenas@ ing.puc.cl Leopold0 Bertossi Pontificia Universidad Cat6lica de Chile Escuela de Ingenieria Departamento de Ciencia de Computaci6n Casilla 306, Santiago 22, Chile bertossi@ing.puc.cl Jan Chomicki Monmouth University Department of Computer Science West Long Branch, NJ 07764 chomicki @monmouth.edu Abstract In this paper we consider the problem of the logical characterization of the notion of consistent answer in a relational database that may violate given integrity constraints. This notion is captured in terms of the possible repaired versions of the database. A rnethod for computing consistent answers is given and its soundness and completeness (for some classes of constraints and queries) proved. The method is based on an iterative procedure whose termination for several classes of constraints is proved as well. 1 Introduction Integrity constraints capture an important normative aspect of every database application. However, it is often the case that their satisfaction cannot be guaranteed, allowing for the existence of inconsistent database instances. In that case, it is important to know which query answers are consistent with the integrity comtraints and which are not. In this paper, we provide a logical characterization of consistent query answers in...
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...F4: DW Architecture and Lifecycle Erik Perjons, DSV, SU/KTH perjons@dsv.su.se The data warehouse architecture The back room The front room Analysis/OLAP Productt Product2 Product3 Product4 Time1 Time2 Time3 Time4 Value1 Value2 Value3 Value4 Value11 Value21 Value31 Value41 Data warehouse External sources Extract Transform Load Serve Query/Reporting Operational source systems Data marts Data mining Falö aöldf flaöd aklöd falö alksdf Operational source Data staging systems (RK) area (RK) Legacy systems Back end tools OLTP/TP systems Data presentation area (RK) ”The data warehouse” Presentation (OLAP) servers Data access tools (RK) End user applications Business Intelligence tools Operational Source Systems Operational source systems characteristics: Operational source systems • the source data often in OLTP (Online Transaction Processing) systems, also called TPS (Transaction Processing Systems) • high level of performance and availability • often one-record-at-a time queries • already occupied by the normal operations of the organisation OLTP vs. DSS (Decision Support Systems) OLTP vs. OLAP (Online analytical processing) Operational Source Systems More operational source systems characteristics: Operational source systems • a OLTP system may be reliable and consistent, but there are often inconsistencies between different OLTP systems • different types of data format and data structures in different OLTP systems AND DIFFERENT...
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...definition and manipulation. Can reconstruct lists from their underlying tables, query for specific data conditions, perform computations, can update/delete/insert data. Database System four components: * Database – collection of related tables and other structures * Database Management System DBMS – computer program used to create, process, and administer the database. Receives requests encoded in SQL and translates them into action on the database. Large complicated program licensed by software vendors. * Database Application – Set of one or more computer programs that serves as an intermediary between the user and the DBMS, These programs read or modify data by sending SQL statements to the DBMS. * Users – use the DB Application to keep track of things. Use forms to read, enter, and query data. Database – defined as self-describing (a description of the structure if the database is contained within the database itself) relational collection of tables. Metadata – data about the structure of the a database. (IE names of tables, names of columns, and the tables in which they belong, properties of tables and columns) Database contents – user data, metadata, indexes, and other overhead data (these improve performance). Application data (describes application elements, such as forms and reports) DBMS examples –...
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...CA218 Introduction to Databases Notes Chapter 4: Entity-Relationship (ER) Data Modelling • • • • • Introduction ER Definitions ER Notation Relationships ER Examples (c) Martin Crane 2011 CA218 Introduction to Databases Notes Introduction to ER Modelling • • • • • An Entity-relationship model (ERM) is an abstract and conceptual representation of data. ER modelling is a DB modelling method, used to produce a type of conceptual schema of a system. Diagrams created by this process are called ER diagrams. Sequence: Conceptual data model (i.e. ER) is, at a later stage (called logical design), mapped to a logical data model, (e.g. relational model); this is mapped to a physical model in physical design. ER Model used to interpret, specify & document requirements for DBs irrespective of DBMS being used. Planning/ Analysis Data Model (ER Diagram) Logical DB Conceptual Design Logical Data Model (Relational, Normal Form) Physical DB Design Physical Data Model (Tables with P., F. Keys etc) Implementation (c) Martin Crane 2011 CA218 Introduction to Databases Notes • Entity (Instance): ER Definitions Student – An instance of a physical object in the real world. – Entity Class: Group of objects of the same type. – E.g. Entity Class “Student”, Entities “John”, “Trish” etc • Attributes: – Properties of Entities that describe their characteristics. – Types: • Simple: Attribute that is not divisible, e.g. age. • Composite: Attribute...
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...HP Universal CMDB Software Version: UCMDB 10.10, CP 13.00 Universal Discovery Content Guide - HP Integrations Document Release Date: November 2013 Software Release Date: November 2013 Legal Notices Warranty The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein. The information contained herein is subject to change without notice. Restricted Rights Legend Confidential computer software. Valid license from HP required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. Copyright Notice © Copyright 1996 - 2013 Hewlett-Packard Development Company, L.P. Trademark Notices Adobe® and Acrobat® are trademarks of Adobe Systems Incorporated. AMD and the AMD Arrow symbol are trademarks of Advanced Micro Devices, Inc. Google™ and Google Maps™ are trademarks of Google Inc. Intel®, Itanium®, Pentium®, and Intel® Xeon® are trademarks of Intel Corporation in the U.S. and other countries. Java and Oracle are registered trademarks of Oracle Corporation and/or its affiliates. Microsoft®, Windows®, Windows NT®, Windows® XP, and Windows...
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