...Started 2 4. ‘Bang for the Buck’ Data Models 2 5. Design Patterns 2 6. Master Data Management (MDM) 2 7. Build your Own 2 8. Generic Data Models 2 9. From the Cradle to the Grave 2 10. Commercial Web Sites 2 11. Vertical Applications 2 Appendix A. Business Rules 2 Appendix B. Glossary of Terms 2 1. Introduction 1.1 Our Approach This book adopts a unique approach which is based on using existing Data Models as the basis for designing new ones to meet specific requirements. We have almost 800 Data Models on our Database Answers Website and they define our starting point – * http://www.databaseanswers.org/data_models/index.htm We have used the Dezign Data Modelling Tool to create most of the Data Models in this book. I chose it because it is powerful, flexible and affordable. Members of the Database Answers Community and people who buy this book can purchase Dezign and benefit from a discount of 25%. In order to gain the benefit of this discount, all you have to do is to send an email to dba_requests@barryw.org with your Database Answers Community ID. We will then send you the order instructions. 1.2 Tutorials We have a number of useful Tutorials on our Website. Here are two of them :- * Data Modelling with two young people visiting Windsor Castle * http://www.databaseanswers.org/tutorial4_data_modelling_dimple_and_toby_visit_windsor_castle/index.htm * Beginner’s Guide to Data Modelling using Dezign – ...
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...dependent (not independent). 5. Logical models show not only what a system is or does, but also how the system is implemented. Answer: False Page: 316 LOD: Medium Rationale: Physical models show not only what a system is or does, but also how the system is implemented; therefore, they are implementation dependent. Logical models are implementation independent. 6. Process modeling is a technique for organizing and documenting the structure and flow of data through a system's processes and /or the logic, policies and procedures to be implemented by a system's processes. Answer: True Page: 317 LOD: Easy 7. A data flow diagram (DFD) is a tool that depicts the flow of data through a system and the work or processing performed by that system. Answer: True Page: 217 LOD: Easy 8. An entity relationship diagram (ERD) is a tool that depicts the flow of data through a system and the work or processing performed by that system. Answer: False Page: 317 LOD: Medium Rationale: A data flow diagram (DFD) is a tool that depicts the flow of data through a system and the work or processing performed by that system. The...
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...Best Practices in Data Modeling Dan English Objectives • • • • • Understand how QlikView is Different from SQL Understand How QlikView works with(out) a Data Warehouse Not Throw Baby out with the Bathwater Adopt Applicable Data Modeling Best Practices Know Where to Go for More Information QlikView is not SQL (SQL Schemas) SQL take a large schema and queries a subset of tables. Each query creates a temporary “Schema” of only a few tables. Query result sets are independent of each other. Query 1 Query 2 QlikView is not SQL (QV Schemas) QlikView builds a smaller and more reporting friendly schema from the transactional database. This schema is persistent and reacts as a whole to user “queries”. A selection affects the entire schema. QlikView is not SQL (Aggregation and Granularity) Store Table Store A B SqrFootage 1000 800 Sales Table Store A A A B B Prod 1 2 3 1 2 Price $1.25 $0.75 $2.50 $1.25 $0.75 Date 1/1/2006 1/2/2006 1/3/2006 1/4/2006 1/5/2006 Select * From Store, Sales Where Store.Store = Sales.Store will return: SqrFootage 1000 1000 1000 800 800 Store A A A B B Prod 1 2 3 1 2 Price $1.25 $0.75 $2.50 $1.25 $0.75 Date 1/1/2006 1/1/2006 1/1/2006 1/1/2006 1/1/2006 Sum(SqrFootage) will return: 4600 If you want the accurate Sum of SqrFootage in SQL you can not join on the Sales table in the same Query! QlikView is not SQL (Benefits) • QlikView allows you to see the results of a selection across the...
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...Discussion Question: 1. When developing a successful data warehouse, what are the most important risks and issues to consider and potentially avoid? Data warehouse projects have many risks. Most of them are also found in other IT projects, but data warehousing risks are more serious because data warehouses are expensive, time-and-resource demanding, large-scale projects. Each risk should be assessed at the inception of the project. When developing a successful data warehouse, it is important to carefully consider various risks and avoid the following issues: • Starting with the wrong sponsorship chain. You need an executive sponsor who has influence over the necessary resources to support and invest in the data warehouse. You also need an executive project driver, someone who has earned the respect of other executives, has a healthy skepticism about technology, and is decisive but flexible. You also need an IS/IT manager to head up the project. • Setting expectations that you cannot meet. You do not want to frustrate executives at the moment of truth. Every data warehousing project has two phases: Phase 1 is the selling phase, in which you internally market the project by selling the benefits to those who have access to needed resources. Phase 2 is the struggle to meet the expectations described in Phase 1. For a mere $1 to $7 million, hopefully, you can deliver. • Engaging in politically naive behavior. Do not simply state that a data warehouse will help managers make better decisions...
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...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 50 2. The Entity-Relationship Model Introduction Database design (3) During DB design, a formal model of the relevant aspects of the real world (“mini...
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...Data modeling -a technique for organizing and documenting a system’s data. Sometimes called database modeling. Entity relationship diagram (ERD) – a data model utilizing several notations to depict data in terms of the entities and relationships described by that data. 8 Data Modeling Concepts: Entity Entity a class of persons, places, objects, events, or concepts about which we need to capture and store data. –Named by a singular noun Persons: agency, contractor, customer, department, division, employee, instructor, student, supplier. Places: sales region, building, room, branch office, campus. Objects: book, machine, part, product, raw material, software license, software package, tool, vehicle model, vehicle. Events: application, award, cancellation, class, flight, invoice, order, registration, renewal, requisition, reservation, sale, trip. Concepts: account, block of time, bond, course, fund, qualification, stock. Data Modeling Concepts: Entity Entity instance – a single occurrence of an entity. 8-6 Student ID | Last Name | First Name | 2144 | Arnold | Betty | 3122 | Taylor | John | 3843 | Simmons | Lisa | 9844 | Macy | Bill | 2837 | Leath | Heather | 2293 | Wrench | Tim | Data Modeling Concepts: Attributes Attribute – a descriptive property or characteristic of an entity. Synonyms include element, property, and field. –Just as a physical student can have attributes, such as hair color, height, etc...
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...Lesson 3: An introduction to data modeling 3.1 Introduction: The importance of conceptual models same: understand the problem before you start constructing a solution. There are two important things to keep in mind when learning about and doing data modeling: 1. Data modeling is first and foremost a tool for communication.Their is no single “right” model. Instead, a valuable model highlights tricky issues, allows users, designers, and implementors to discuss the issues using the same vocabulary, and leads to better design decisions. 2. The modeling process is inherently iterative: you create a model, check its assumptions with users, make the necessary changes, and repeat the cycle until you are sure you understand the critical issues. In this background lesson, you are going to use a data modeling technique—specifically, EntityRelationship Diagrams (ERDs)—to model the business scenario from Lesson 2. The data model you create in this lesson will form the foundation of the database that you use throughout the remaining lessons. Before you sit down in front of the keyboard and start creating a database application, it is critical that you take a step back and consider your business problem—in this case, the kitchen supply scenario presented in Lesson 2— from a conceptual point of view. To facilitate this process, a number of conceptual modeling techniques have been developed by computer scientists, psychologists, and consultants. ? For our purposes, we can think of a...
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...Encyclopedia of Database Systems, Ling Liu and M. Tamer Özsu (Eds.), 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...
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...ranow, E. B. “Developing Good Data Definitions.” Database Programming & Design 2 (8) (1989): 36–39. Booch, G. Object-Oriented Analysis and Design with Applications. 2d ed. Redwood City, CA: Benjamin Cummings, 1994. Bruce, T. A. Designing Quality Databases with IDEF1X Information Models. New York: Dorset House, 1992. Chen, P. P-S. “The Entity-Relationship Model—Toward a Unified View of Data.” ACM Transactions on Database Systems 1 (March 1976): 9–36. Codd, E. F. “A Relational Model of Data for Large Relational Databases.” Communications of the ACM 13 (6) (1970): 77–87. Dutka, A. F., and H. H. Hanson. Fundamentals of Data Normalization. Reading, MA: Addison-Wesley, 1989. Finkelstein, R. “Breaking the Rules Has a Price.” Database Programming & Design 1 (June 1988): 11–14. Fleming, C. C., and B. von Halle. “An Overview of Logical Data Modeling.” Data Resource Management 1 (1) (1990): 5–15. Fowler, M. UML Distilled: A Brief Guide to the Object Modeling Language. 2d ed. Reading, MA: Addison-Wesley, 2000. Gibson, M., C. Hughes, and W. Remington. “Tracking the Trade-Offs with Inverted Lists.” Database Programming & Design 2 (January 1989): 28–34. Gottesdiener, E. “Turning Rules into Requirements.” Application Development Trends 6 (7) (1999): 37–50. Hay, D. Data Model Patterns: Conventions of Thought. New York: Dorset House, 1996. Hoffer, J. A., V. Ramesh, and H. Topi. Modern Database Management. 10th ed. Upper Saddle River, NJ: Prentice Hall, 2011. Inmon, W. H...
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...COMPARING PERCEPTIONS OF THE SYSTEMS ANALYSIS AND DESIGN COURSE BRANDI N. GUIDRY University of Louisiana at Lafayette Lafayette, LA 70504 DAVID P. STEVENS University of Louisiana at Lafayette Lafayette, LA 70504 ABSTRACT Information Systems (IS) practitioners and educators have equal interest in the content of the Systems Analysis and Design Course (“SAD”). Previous research has examined instructors’ perceptions regarding the skills and topics that are most important in the teaching of the SAD course and the class time devoted to each. A similar assessment evaluated SAD course content from a practitioner perspective. Both studies used entropy calculations. A comparison of these studies is presented in this paper. For traditional topics, the group (either faculty or practitioner) with greater agreement believes the topic to be deserving of less class time. For structured and object-oriented topics, the group with the greater agreement also believes the topic to be of greater importance. This analysis demonstrates that practitioners and academics agree on approximately 40% of the SAD skills and knowledge areas. Keywords: Systems analysis and design, Structured analysis, Object-oriented analysis, Management Information Systems curricula, Entropy INTRODUCTION It is important that an education in Management Information Systems (MIS) is reflective of practices and techniques that are currently used in industry. Given the pace of technological innovation, there are ever-changing...
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...should know (by chapter): * AIS, audit trail, business intelligence, dashboard, e-business, ERP, ISACA, KPI, REA, SAR, sustainability reporting, VARs * GUI, MICR, operating system, OCR, pixels, POS, primary memory, RAID, secondary memory, SAAS, turnaround documents * Agent, attributes, event, cardinality, concurrency, field, data modeling, DBA, DBMS, entity, E-R diagram, foreign key, 1NF, 2NF, 3NF, record, relationship, table, transaction file, transitive dependency * DDL, DML, default value, field properties, input mask, query, referential integrity, schema, SQL, validation rule * Bound control, calculated field, control break, tab order, unbound control You should be able to: * Describe an accounting information system * Distinguish between data and information * Discuss how IT has impacted areas in accounting * Discuss why IT is important to accountants * Discuss the potential impact of an AIS on how accountants work * Describe the data hierarchy in computer systems * Contrast a data warehouse with an operational database * Compare three techniques for capturing and recording accounting data * Define the word entity as used in entity-relationship diagrams * Discuss pros and cons of cloud computing * List and describe 4 ways a...
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...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 Although the field of information systems engineering is young relative to most other engineering disciplines, it does apply formal modeling methods to study and predict aspects of a planned system. Different kinds of models may exhibit the user interfaces, behaviours, or data interchanges of the planned system. Modern businesses depend heavily on timely, trustworthy, and relevant data to provide a competitive advantage (Lau, 2010). As a result, organizations invest in modeling their enterprise data. Data models describe the logical and physical structure of data that the information systems maintain and process. The main goal of data modeling is to identify all of the data elements that the enterprise uses to manage its business, along with the structure and interrelationships of these elements. Data modeling typically follows activity modeling, which defines the functional requirements for the system. Its focus is to build a standard representation for the system’s data elements with little regard for when components...
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...Project Outline Project Overview This project will go over the process of designing a database. The database that will be designed will be a database for a typical retail store. The purpose of this database will be to manage and store the data produced or collected during normal day to day operations. Throughout the rest of this project the information and processes will be aimed toward the creation of this retail store database. This is to help provide an example of what is needed to create a database and how each process or step corresponds to each other. Section 2: Description of the Database Design Life Cycle Database Design Life Cycle In order to create a database you must understand that there are certain steps that are contained within the Database Design Life Cycle (DBLC). These seven steps help you design the database and they give a step by step process to guide you through the phases of development. These steps are listed as follows: 1. Defining a mission statement and mission objectives 2. Analyzing the current database 3. Creating the data structures 4. Determining and establishing table relationships 5. Determining and defining business rules 6. Determining and defining views 7. Reviewing data integrity The first step in the DBLC is to define a mission statement and the mission objectives. The...
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...candidate for your organization. Let me explain to you how I can improve upon the current schema for the company’s new restaurant using DBMS. First of all let me explain what I know is DBMS; it’s software that allows data to be manipulated, stored, and retrieved from the data stored which can be accessed by multiple users. The application programs used for those operations are Microsoft Access, SQL Server, and Oracle. The advantages of a DBMS are maintaining what terms are used to search by therefore making searches quick and easy, keeps control of data redundancy (it’s a process from 1NF to 2NF to 3NF), information security feature with keeping those that require certain access to data, has the automatic functions necessary to save and recall data for back up recovery, it makes sure that data can be accessed through any application that the company will use, there are different interfaces for users to get to the data that they need to get to, and it uses whatever rules that the company wants to enforce to ensure data continuity. As you can see there are a plethora of advantages of a DBMS. Now I will explain the Flat File System that you are currently using and its disadvantages. A Flat File System is such as using Microsoft Excel is basically storing all data in one directory. Some disadvantages are almost no security which means you could put a password to access the...
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...MGMT 340 ALL QUIZZES WEEK 1 TO 7 To purchase this visit following link: http://www.activitymode.com/product/mgmt-340-all-quizzes-week-1-to-7/ Contact us at: SUPPORT@ACTIVITYMODE.COM MGMT 340 ALL QUIZZES WEEK 1 TO 7 MGMT 340 All Quizzes Week 1 To 7 MGMT 340 Week 1 : The Systems Development Environment – Quiz 1. Question : (TCO 1) The information system includes all of the following EXCEPT 2. Question : (TCO 1) The process of breaking the description of a system down into its smaller components best defines 3. Question : (TCO 1) The extent to which a system or subsystem performs a single function defines 4. Question : (TCO 1) A centralized database that contains all diagrams, forms and report definitions, data structure, data definitions, process flows and logic, and definitions of other organizational and system components best describes 5. Question : (TCO 3) In which SDLC phase will the analyst study the organization’s current procedures and the information systems used to perform tasks? 6. Question : (TCO 3) Priorities for systems and projects are deliverables for the 7. Question : (TCO 3) A systems development methodology created to radically decrease the time needed to design and implement information systems best describes 8. Question : (TCO 3) The practice of turning over responsibility of some or all of an organization’s information systems applications and operations to an outside firm is referred to as 9. Question : (TCO 3) An organization should acquire...
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