Underlined attributes are the primary keys bolded attributes are foreign keys CUSTOMER (Cus_id, cus_last, cus_first, staddr, zipcode) EMPLOYEE (Emp_id, emp_first, emp_last, staddr, zipcode) VIDEO (Isbn, title, vid_length, rate_id, genre_type, release_date) GENRE (Genre_type, genre_description) ACTOR (Act_id, First, Last) ACT_IN (Isbn, Act_id) COPY1 (Cid,Isbn, Copy_no, rent_type) RENT_DURATION (Rent_No, rent_type, no_days, rent_charge) RENT_QUALITY (Rent_type, type_description) RATING
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COMM 226 Database Systems INTRODUCTION A database is a structured collection of data, and is usually stored electronically to facilitate computerassisted search and retrieval. The electronic format allows different users to have views of the data that serve their particular needs. Furthermore, the database management software can ensure the consistency, integrity, and security of the database, provided the data needs of the organization have been correctly modeled and implemented. DATA MODELING
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Chapter 4 Logical Database Design and the Relational Model 1 Objectives • • • • Define terms for the relational data model Brief introduction to SQL Transform E-R diagrams to relations Create tables with entity and relational integrity constraints 2 Steps in Database Problem Solving Study and Analyze w/Team Interviews & Integrated Model Conceptual Model (E-R) Transformation (Six Cases) Logical M d l L i l Model (Relations) Normalization (Three Steps) Logical Model (3NF Relations) IMPLEMENTATION
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Fundamentals of Database Systems Preface....................................................................................................................................................12 Contents of This Edition.....................................................................................................................13 Guidelines for Using This Book.........................................................................................................14 Acknowledgments ....
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® OCA Oracle Database 11g: SQL Fundamentals I Exam Guide (Exam 1Z0-051) ABOUT THE AUTHORS John Watson (Oxford, UK) works for BPLC Management Consultants, teaching and consulting throughout Europe and Africa. He was with Oracle University for several years in South Africa, and before that worked for a number of companies, government departments, and NGOs in England and Europe. He is OCP qualified in both database and Application Server administration. John is the author of several books
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transactions over a multi-DBMS while dealing with concurrency control and recovery are highlighted, such as site failure, network failure, and time failure. This study proposes an exceptional distributed transaction model for processing transaction queries in multi-DBMS based on the idea that a complete database can be constructed at any stage. Index Terms— Database management system (DBMS), distributed transaction, transaction management, transaction network —————————— —————————— 1 INTRODUCTION
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DOING EMOTIONAL LABOUR: DEALING WITH IRATE AND MESSY GUESTS The reception section had to deal with multifarious demands and queries by guests: ‘the front desk is more pressured [than switchboard], they get millions of questions’ (Guest Services Manager). This constant questioning regularly involved being on the receiving end of complaints, or as one woman who had transferred into the front desk from another department described it, ‘when you’re actually at the front desk, you get it’ (FDA1).5 As
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WHITE P APER Big Data: Trends, Strategies, and S AP Technology Sponsored by: SAP Carl W. Olofson August 2012 Dan Vesset THE DAWN OF THE INTE LLIGENT ECONOMY The intelligent economy has arrived. The convergence of intelligent devices, social networking, pervasive broadband communications, and analytics is redefining relationships among producers, distributors, and consumers of goods and services. The growth in volume, variety, and velocity of data has created new challenges and opportunities
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(RDBMS), catalog, schema, data definition language (DDL), data manipulation language (DML), data control language (DCL), scalar aggregate, vector aggregate, base table, virtual table, dynamic view, and materialized view. ■ ■ ■ ■ ■ Visit www.pearsonhighered.com/ hoffer to view the accompanying video for this chapter. Interpret the history and role of SQL in database development. Define a database using the SQL data definition language. Write single-table queries using SQL commands. Establish referential
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DLSU Engineering e-Journal Vol. 1 No. 1, March 2007, pp. 138-150 Automated Inventory System Using Portable Data Acquisition Module for Bell Electronics Corporation Zarina Ira V. Bernabe Monchie C. Dela Cruz Karen K. Jao Department of Electronics and Communications Engineering De La Salle University, Manila email: ira.bernabe@yahoo.com, chie08_elx@yahoo.com, karenjao@yahoo.com, Jingel A. Tio, Antonio S. Gonzales Jr. Department of Electronics and Communications Engineering De La Salle University
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