...You don’t have to be tall and super thin. No matter what you look like: You too can become a Model! There are different types of models and you have to be realistic in your expectations! There are fashion models, teen models, plus size models, and commercial models. Whenever you look at any magazine, or newspaper ad that is not geared towards fashion you see commercial models. And commercial models look like normal everyday people. As a commercial model, you are not going to get rich. At least most people won’t. But it can be fun part-time work with benefits such as free clothes, great pictures, and usually local recognition. Last night, I participated in Aaron Marcus' Tele-seminar entitled "How to Get Acting and Modeling Jobs and Find Modeling Agencies". The seminar lasted about an hour. You could call in and watch it over the Internet. Aaron offers workshops that you can attend live, but of course he doesn’t come to Birmingham, AL Some of the things that Aaron covered in his seminar were: * How to be a model regardless to what you look like. * What it takes to be a working model. * What to focus on when starting out. You see commercial models in many types of ads. Everyday people are used all of the time posing as Doctors, Lawyers, Teachers, Athletes, etc. Figure out what look you fit and target your career at those types of roles. Once you figure out what type of model that you can be, practice, practice, practice. Gather pictures of looks...
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...Database Modeling and Design: Logical Design 4th Edition Toby Teorey, Sam Lightstone, Tom Nadeau Lecture Notes Contents I. Introduction ................................................................………...……2 Relational database life cycle 3 Characteristics of a good database design process 6 II. The Entity-Relationship (ER) Model …………...……………….7 Basic ER concepts 7 Ternary relationships 11 III. The Unified Modeling Language (UML)………...…………….13 Class diagrams 13 Activity diagrams 19 Rules of thumb for UML 21 IV. Requirements Analysis and Conceptual Data Modeling….…..22 Requirements analysis 22 Conceptual data modeling 24 View integration methods 25 Entity Clustering 30 V. Transforming the Conceptual Model to SQL…………...………32 VI. Normalization and normal forms ………………………………38 First normal form to third normal form (3NF) and BCNF 38 3NF synthesis algorithm (Bernstein) 43 VII. An Example of Logical Database Design………………………48 VIII. Business Intelligence………………………………..……….....52 Data warehousing 52 On-line analytical processing (OLAP) 58 IX. CASE Tools for Logical Database Design……………………….60 I. Introduction Introductory Concepts data—a fact, something upon which an inference is based (information or knowledge has value, data has cost) data item—smallest named unit of data that has meaning in the real world (examples: last name, address, ssn, political...
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...CIV E 603: Information Modeling and Database Systems Lecture 1 1 What to Study? Introduction to Data base Relational Model Database design Structured Query Language (SQL) 22 Let’s begin the journey !! …. in to fascinating world of databases 23 Today’s outline Database Management System (DBMS) Entity-Relationship (ER) Model 24 What is a database? Many people would like to call it organization… 25 What is a database? Database is a structured collection of related data. Many name it efficiency… 26 A database is A home for data – since that is where data stay… A manager for data – since data are organized neatly… A GOOGLE for data – since a particular record can be found in a snap… A guardian for data – since a database rejects malicious accesses… … 27 What is a Database? Database: is a collection of related data Data: known facts that can be recorded and that have implicit meaning Properties of database: • represents some aspect of the real world (mini-world -UoD) • logically coherent collection of data with some inherent meaning. A random assortment of data cannot correctly be referred to as a database. • designed, built, and populated with data for a specific purpose. It has an intended groups of users. 28 What is a Database? A database can be of any size and of varying complexity. • For example, the list of...
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...Official TCC Course Syllabus Discipline Prefix: ITD Credit Hours: 4 Contact Hours: 4 Course Number: 260 Course Section: H01B Lecture Hours: 4 Studio Hours: Clinical Hours: Semester: Fall 2014 Lab Hours: Course Title: Database Modeling and Design Meeting Days/Time/Location: Wednesday, 8:00 pm – 9:40 pm, ATC – H207 Instructor Information Name: John Clary Office Location: ATC – H207 Office Hours: Immediately before and after class, other times and locations by appointment Contact Information: jclary@tcc.edu Blackboard site: http://learn.vccs.edu Course Information Course Description Introduces life cycle application development methodologies in a systematic approach to developing relational databases and designing applications. Presents content introducing functional and business process modeling, using modeling information to produce application designs, analyzing data requirements as entities, attributes, and relationships and map an entity relationship diagram to an initial database design. Identifies the available automated development tools and software to perform practical applications of these concepts. Prerequisites and/or Co-requisites ITD132 – Structured Query Language General Education Core Competencies Supported by this Course • Critical Thinking A competent critical thinker evaluates evidence carefully and applies reasoning to decide what to believe and how to act. Page 1 of 8 • Information Literacy A person who is competent in information...
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...enhance the practical coverage of concepts in an introductory database systems course. The material presented in this laboratory manual complement many of the chapters of the Elmasri/Navathe text typically covered in most introductory database systems courses. Chapter Mappings The laboratory manual consists of 8 chapters and the following table shows the mapping to the chapters in the Elmasri/Navathe textbook: Laboratory Manual Chapter Elmasri/Navathe 6th Edition Chapter(s) Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Chapters 7, 8, and 9 Chapters 3, 6, and 26 Chapters 4, 5, and 13 Chapters 4, 5, and 14 Chapters 15 and 16 Chapter 11 Chapter 12 Chapters 13 and 14 Chapter 1 presents ERWin, a popular data modeling software that allows database designers to represent Entity-Relationship diagrams and automatically generate relational SQL code to create the database in one of several commercial relational database management systems such as Oracle or Microsoft SQLServer. The material presented in this chapter is tutorial in nature and covers the COMPANY database design of the Elmasri/Navathe text in detail. Chapter 2 presents three interpreters that can be used to execute queries in Relational Algebra, Domain Relational Calculus, and Datalog. These interpreters are part of a Java package that includes a rudimentary database engine capable of storing relations and able to perform basic relational...
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...Information Systems Lecture Notes G´bor Bodn´r a a RISC-Linz, Johannes Kepler University, A-4040 Linz, Austria email: Gabor.Bodnar@risc.uni-linz.ac.at www: http://www.risc.uni-linz.ac.at/people/gbodnar January 23, 2005 2 Contents 0 Introduction 0.1 Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 Information Sources . . . . . . . . . . . . . . . . . . . . . . . . . 1 Data Modeling 1.1 Introduction . . . . . . . . . . . . . . . . . 1.2 The Entity-Relationship Model . . . . . . 1.2.1 Entities, Attributes, Relationships 1.2.2 Classification of Relationships . . . 1.2.3 Keys . . . . . . . . . . . . . . . . . 1.2.4 Entity-Relationship Diagrams . . . 1.2.5 Entity-Relationship Design . . . . 1.2.6 Exercises . . . . . . . . . . . . . . 1.3 The Relational Model . . . . . . . . . . . 1.3.1 Relational Structure . . . . . . . . 1.3.2 Relational Algebra . . . . . . . . . 1.3.3 Functional Dependencies . . . . . . 1.3.4 Normal forms . . . . . . . . . . . . 1.3.5 Indexing and Hashing . . . . . . . 1.3.6 Exercises . . . . . . . . . . . . . . 1.4 SQL . . . . . . . . . . . . . . . . . . . . . 1.4.1 Data Definition . . . . . . . . . . . 1.4.2 Simple Queries . . . . . . . . . . . 1.4.3 Database Modification . . . . . . . 1.4.4 Views and Joins . . . . . . . . . . 1.4.5 Embedded SQL . . . . . . . . . . . 1.4.6 Exercises . . . . . . . . . . . . . . 2 Information Systems On-Line 2.1 On-Line Databases . . . . . . . . . . . 2.1.1 Security Control . . . . . . . . 2.1.2 Transaction...
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...This page intentionally left blank Te n t h E d i t i o n MODERN DATABASE MANAGEMENT Editorial Director: Sally Yagan Editor in Chief: Eric Svendsen Executive Editor: Bob Horan Editorial Project Manager: Kelly Loftus Editorial Assistant: Jason Calcano Director of Marketing: Patrice Lumumba Jones Marketing Manager: Anne Fahlgren Marketing Assistant: Melinda Jensen Senior Managing Editor: Judy Leale Project Manager: Becca Richter Senior Operations Supervisor: Arnold Vila Operations Specialist: Ilene Kahn Senior Art Director: Jayne Conte Cover Designer: Suzanne Behnke Cover Art: Fotolia © vuifah Manager, Visual Research: Karen Sanatar Permissions Project Manager: Shannon Barbe Media Project Manager, Editorial: Denise Vaughn Media Project Manager, Production: Lisa Rinaldi Supplements Editor: Kelly Loftus Full-Service Project Management: PreMediaGlobal Composition: PreMediaGlobal Printer/Binder: Edwards Brothers Cover Printer: Lehigh-Phoenix Color/Hagerstown Text Font: Palatino Credits and acknowledgments borrowed from other sources and reproduced, with permission, in this textbook appear on appropriate page within text. Microsoft® and Windows® are registered trademarks of the Microsoft Corporation in the U.S.A. and other countries. Screen shots and icons reprinted with permission from the Microsoft Corporation. This book is not sponsored or endorsed by or affiliated with the Microsoft Corporation. Copyright © 2011, 2009, 2007, 2005, 2002...
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...Table of Contents 1. Introduction 1 2. Analysis for problems associated with using models 1 2.1. Model error 1 2.1.1. Wrong or simplifying assumptions 1 2.1.2. Over dependence on historical data 3 2.1.3. Black swans 4 2.2. Implementing a model wrongly 4 3. Improvements of the usage of models 5 4. Conclusion 7 1. Introduction The financial sector plays crucial roles that mobilize savings and allocate credit in economic performance. In recent years, there has been significant technological development within the financial sector, which has enable banks to effectively manage their internal risk through the application of risk models. The use of models to measure risks is the preferred approach by most banks, for example Goldman Sachs applies the Value at Risk model. However, according to Office of the Comptroller of the Currency (2011, p1), “the expanding use of models in all aspects of banking reflects the extent to which models can improve business decisions, but models also come with costs”. Besides, in a recent study (Jorion 2009), it is argued that many financial institutions experienced large losses over the past few decades due to limitations of using sophisticated models. Therefore, it is essential for Andrew Bank Ltd. to have an in-depth understanding of disadvantages relating to using models and solutions to improve these model risks. 2. Analysis for problems associated with using...
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...DATABASE S YSTEMS DESIGN, IMPLEMENTATION, AND MANAGEMENT CARLOS CORONEL • STEVEN MORRIS • PETER ROB Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Database Systems: Design, Implementation, and Management, Ninth Edition Carlos Coronel, Steven Morris, and Peter Rob Vice President of Editorial, Business: Jack W. Calhoun Publisher: Joe Sabatino Senior Acquisitions Editor: Charles McCormick, Jr. Senior Product Manager: Kate Mason Development Editor: Deb Kaufmann Editorial Assistant: Nora Heink Senior Marketing Communications Manager: Libby Shipp Marketing Coordinator: Suellen Ruttkay Content Product Manager: Matthew Hutchinson Senior Art Director: Stacy Jenkins Shirley Cover Designer: Itzhack Shelomi Cover Image: iStock Images Media Editor: Chris Valentine Manufacturing Coordinator: Julio Esperas Copyeditor: Andrea Schein Proofreader: Foxxe Editorial Indexer: Elizabeth Cunningham Composition: GEX Publishing Services © 2011 Cengage Learning ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted...
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...Fundamentals of Database Systems Preface....................................................................................................................................................12 Contents of This Edition.....................................................................................................................13 Guidelines for Using This Book.........................................................................................................14 Acknowledgments ..............................................................................................................................15 Contents of This Edition.........................................................................................................................17 Guidelines for Using This Book.............................................................................................................19 Acknowledgments ..................................................................................................................................21 About the Authors ..................................................................................................................................22 Part 1: Basic Concepts............................................................................................................................23 Chapter 1: Databases and Database Users..........................................................................................23 ...
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...UCSB Computer Science Technical Report 2010-05. Who’s Driving this Cloud? Towards Efficient Migration for Elastic and Autonomic Multitenant Databases Aaron Elmore Sudipto Das Divyakant Agrawal Amr El Abbadi Department of Computer Science University of California, Santa Barbara, CA, USA {aelmore, sudipto, agrawal, amr}@cs.ucsb.edu Abstract The success of cloud computing as a platform for deploying webapplications has led to a deluge of applications characterized by small data footprints but unpredictable access patterns. An autonomic and scalable multitenant database management system (DBMS) is therefore an important component of the software stack for platforms supporting these applications. Elastic load balancing is a key requirement for effective resource utilization and operational cost minimization. Efficient techniques for database migration are thus essential for elasticity in a multitenant DBMS. Our vision is a DBMS where multitenancy is viewed as virtualization in the database layer, and migration is a first class notion with the same stature as scalability, availability etc. This paper serves as the first step in this direction. We analyze the various models of database multitenancy, formalize the forms of migration, evaluate the offthe-shelf migration techniques, and identify the design space and research goals for an autonomic and elastic multitenant database. Categories and Subject Descriptors H.2.4 [Database Management]: Systems—Relational...
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...Springer-Verlag, 2009. Synonyms computational ontology, semantic data model, ontological engineering Definition In the context of computer and information sciences, an ontology defines a set of representational primitives with which to model a domain of knowledge or discourse. The representational primitives are typically classes (or sets), attributes (or properties), and relationships (or relations among class members). The definitions of the representational primitives include information about their meaning and constraints on their logically consistent application. In the context of database systems, ontology can be viewed as a level of abstraction of data models, analogous to hierarchical and relational models, but intended for modeling knowledge about individuals, their attributes, and their relationships to other individuals. Ontologies are typically specified in languages that allow abstraction away from data structures and implementation strategies; in practice, the languages of ontologies are closer in expressive power to first-order logic than languages used to model databases. For this reason, ontologies are said to be at the "semantic" level, whereas database schema are models of data at the "logical" or "physical" level. Due to their independence from lower level data models, ontologies are used for integrating heterogeneous databases, enabling interoperability among disparate systems, and specifying interfaces to independent, knowledge-based services. In the...
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...does a 3D printer work? Before the 3D printer was developed, the 2D printer was still a fascinating machine to many people. With a 2D printer, what was printed out on a piece of paper was put together and designed on a computer program such as Microsoft Word or Presentations. The file that the printed image or information was created in holds the instructions that the printer is to follow. A 3D printer also needs a file and instructions to print. The goods or designs that are printed can be customized, because altering them will not require complete retooling, only slightly adjusting the instructions in the software. The file is known as a Computer Aided Design (CAD) or Computer-Aided Manufacturing (CAM) file that requires the use of a 3D modeling program, or with a 3D model using a 3D scanner. This software quickly slices the model or design on the program into hundreds or thousands of thin-sliced, horizontal layers. The layers get printed one by one atop of one another until the 3D object is complete. Owners of 3D printers can choose between 2 types of plastic strands: acrylonitrile butadiene styrene (ABS) or polylactic acid (PLA). Some 3D printers can use both kinds of plastic, while others only work with one. These plastics are available on spools with plastic strands/strings that are usually 1.75 millimeters thick or 3 millimeters thick. Gears work to pull the filament through the print head. Immediately before it is pushed through the pointed nozzle, the filament it pushed...
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...data - known facts that can be recorded and that have implicit meaning. Database - represents some aspect of the real world (miniworld or universe of discource – UoD). Collection of related data (a random assortment of data is not a database). A DB is designed, built, and populated with data for a specific purpose. It has an intended group of users and a some preconceived applications in which the users are interested. DBMS - is a collection of programs that enables users to create and maintain a database. database system – it is a combination of database and DBMS software. program – data independence – The structure of data files is stored in the DBMS catalog separately from the access programs. user view - – includes a number of external schemas that describes the part of the database that a particular user group is interested in and hides the rest of the database from that user group. DBA – is an IT professional that is responsible for Installation, Configuration, Upgrade, Administration, Monitoring, Maintenance and Securing of databases in an organization. The chief administrator of the database. end user - are the people whose jobs require access to the database for querying, updating, and generating reports; the database primarily exists for their use. data model - a collection of concepts that can be used to describe the structure of a database-provides the necessary means to achieve this abstraction. database schema - of a database system is its structure described...
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...Define each of the following: a. Base table: Is a relational data model that contains stored records; it corresponds to relations that are identified in the database conceptual schema. b. Data definition language(DDL) Commands used to define a database, including creating, altering, and dropping tables and establishing constraints. c. data manipulation language(DML) Commands used to maintain and query a database, including those for updating, inserting, modifying, and querying data. d. dynamic view: A virtual table that is created dynamically upon request by a user. Its a definition that is stored in the system catalog, and the contents of the view are materialized as a result of an SQL query that uses the view. e. materialized view: Copies of data, based on SQL queries. A materialized view exists as a table and must be kept synchronized with its associated tables. f. referential integrity constraint: A rule that states that either each foreign key value must match a primary key value in another relation or the foreign key value must be null. g. relational DBMS (RDBMS): A database management system that manages data as a collection of tables in which all data relationships are represented by common values in related tables. h. schema: A structure that contains descriptions of objects created by a user, such as base tables, views, and constraints, as part of a database. i. virtual table: A table constructed automatically as needed by a DBMS...
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