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Fundamentals & Ethics of Information Systems IS 201

Fundamentals & Ethics of Information Systems IS 201. Chapter 4 Organizing Data and Information Databases and Database Management Systems. Learning Objectives. Define general data management concepts and terms Highlight the advantages of the database approach to data management

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Fundamentals & Ethics of Information Systems IS 201

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  1. Fundamentals & Ethics of Information SystemsIS 201 Chapter 4 Organizing Data and Information Databases and Database Management Systems Chapter 4 – Organizing Data and Information Slide 1

  2. Learning Objectives • Define general data management concepts and terms • Highlight the advantages of the database approach to data management • Describe the relational database model and outline its basic features • Identify the common functions performed by all database management systems and identify popular user database management systems • Identify and briefly discuss current database applications Chapter 4 – Organizing Data and Information Slide 2

  3. Chapter Overview • Why Learn About Database Systems? • What is a Database? • The Hierarchy of Data • The Database Approach • Data Modeling • Database Management Systems (DBMS) • Data Warehouses, Data Marts, and Data Mining • Business Intelligence • Online Analytical Processing (OLAP) • Object-Oriented Databases • Summary Chapter 4 – Organizing Data and Information Slide 3

  4. 1. Why Learn About Database Systems? • Database systems process and organize large amounts of data • Database systems organize all transactions and services in our societies • Examples • Student registration database system • Bank accounts database system • Hospital patient record database system Chapter 4 – Organizing Data and Information Slide 4

  5. 2. What is a Database? • Database (DB): an organized collection of data • Database Management System (DBMS): group of programs to: • Manages and Manipulates database • Provides an interface between database and user and other application programs • Database administrator (DBA): skilled IS professional who directs all activities related to an organization’s database Chapter 4 – Organizing Data and Information Slide 5

  6. Data Management • Without data and the ability to process it, an organization could not successfully complete most business activities • Data consists of raw facts • For data to be transformed into useful information, it must first be organized in a meaningful way Chapter 4 – Organizing Data and Information Slide 6

  7. 3. The Hierarchy of Data • Bit (a binary digit): a circuit that is either on or off • Byte: eight bits • Character: basic building block of information • Each byte represents a character • Can be an uppercase letter, lowercase letter, numeric digit, or special symbol • Field: typically a name, number, or combination of characters that describes an aspect of a business object or activity Chapter 4 – Organizing Data and Information Slide 7

  8. The Hierarchy of Data (cont.) • Record: a collection of related data fields • File: a collection of related records • Database: a collection of integrated and related files • Hierarchy of data: bits, characters, fields, records, files, and databases Chapter 4 – Organizing Data and Information Slide 8

  9. The Hierarchy of Data (cont.) The Hierarchy of Data Chapter 4 – Organizing Data and Information Slide 9

  10. Data Entities, Attributes, and Keys • Entity: a generalized class of people, places, or things for which data is collected, stored, and maintained (students, teachers, employees, …) • Attribute: characteristic of an entity • Data item (value): value of an attribute • Primary key: field or set of fields that uniquely identifies the record Chapter 4 – Organizing Data and Information Slide 10

  11. Data Entities, Attributes, and Keys (cont.) Keys and Attributes Chapter 4 – Organizing Data and Information Slide 11

  12. 4. The Database Approach • Traditional approach to data management: separate data files are created for each application • Results in data redundancy (duplication) • Data redundancy conflicts with data integrity • Database approach to data management: pool of related data is shared by multiple applications • Significant advantages over traditional approach Chapter 4 – Organizing Data and Information Slide 12

  13. DB Approach The Database Approach to Data Management Chapter 4 – Organizing Data and Information Slide 13

  14. DB Approach (cont.) Advantages of the Database Approach Chapter 4 – Organizing Data and Information Slide 14

  15. DB Approach (cont.) Advantages of the Database Approach (continued) Chapter 4 – Organizing Data and Information Slide 15

  16. DB Approach (cont.) Disadvantages of the Database Approach Chapter 4 – Organizing Data and Information Slide 16

  17. 5. Data Modeling • Data model: a diagram of data entities and their relationships • Entity-relationship (ER) diagrams: data models that use basic graphical symbols to show the organization of and relationships between data entities Chapter 4 – Organizing Data and Information Slide 17

  18. Data Modeling (cont.) Entity Relationship An Entity-Relationship (ER) Diagram for a Customer Order Database Chapter 4 – Organizing Data and Information Slide 18

  19. Data Modeling (cont.) A Simplified ER Diagram Showing the Relationship Between the Manager, Department, and Project Tables Chapter 4 – Organizing Data and Information Slide 19

  20. DB Design • Building a database requires two types of designs • Logical design • Abstract model of how data should be structured and arranged to meet an organization’s information needs • Physical design • Fine-tunes the logical database design for performance and cost considerations Chapter 4 – Organizing Data and Information Slide 20

  21. Building DB • When building a database, consider: • Content: What data should be collected, at what cost? • Access: What data should be provided to which users and when? • Logical structure: How should data be arranged to make sense to a given user? • Physical organization: Where should data be physically located? Chapter 4 – Organizing Data and Information Slide 21

  22. Database Models • Flat file Databases • Plain text files usually contain one record per line • Fields can be separated by delimiters such as comma or tab characters • Relational Databases • 2-D tables • Each row represents a record • Each column represents an attribute • Object oriented Databases Chapter3 – Binary Number System Slide 22

  23. The Relational Database Model • Relational model: all data elements are placed in two-dimensional tables, which are the logical equivalent of files • In the relational model • Each table is an entity • Each row of a table represents a record • Columns of the table represent attributes • Domain: the allowable values for data attributes Chapter 4 – Organizing Data and Information Slide 23

  24. The Relational Database Model (cont.) A Relational Database Model Chapter 4 – Organizing Data and Information Slide 24

  25. Manipulating Data • Selecting: eliminates rows according to criteria • Projecting: eliminates columns in a table • Joining: combines two or more tables • Linking: relates or links two or more tables using common data attributes Chapter 4 – Organizing Data and Information Slide 25

  26. Linking Data Linking Data Tables to Answer an Inquiry Chapter 4 – Organizing Data and Information Slide 26

  27. 6. Database Management Systems (DBMS) • DBMS: a group of programs used as an interface between a database and application programs or a database and the user • Creating and implementing the right DBMS ensures that the database will support both business activities and goals Application DBMS user DB Chapter 4 – Organizing Data and Information Slide 27

  28. Overview of Database Types • Single user • Only one person can use the database at a time • Examples: Access, FileMaker, and InfoPath • Multiple user • Allows dozens or hundreds of people to access the same database system at the same time • Examples: Oracle, Sybase, and IBM Chapter 4 – Organizing Data and Information Slide 28

  29. DB schema • Schema: description of the entire database • Large database systems typically use schemas to define the tables and other database features associated with a person or user Chapter 4 – Organizing Data and Information Slide 29

  30. Creating a DB schema • Data Definition Language (DDL) • Collection of instructions/commands that define and describe data and data relationships in a database • Data dictionary: a detailed description of all the data used in the database Chapter 4 – Organizing Data and Information Slide 30

  31. Using DDL to define schema Using a Data Definition Language to Define a Schema Chapter 4 – Organizing Data and Information Slide 31

  32. Data Dictionary A Typical Data Dictionary Entry Chapter 4 – Organizing Data and Information Slide 32

  33. Storing and Retrieving Data • When an application requests data from the DBMS, the application follows a logical access path • When the DBMS goes to a storage device to retrieve the requested data, it follows a path to the physical location (physical access path) where the data is stored Chapter 4 – Organizing Data and Information Slide 33

  34. Storing and Retrieving Data (cont.) Logical and Physical Access Paths Chapter 4 – Organizing Data and Information Slide 34

  35. Manipulating Data and Generating Reports • Query-By-Example (QBE):a visual approach to developing database queries or requests • Data Manipulation Language (DML): commands that manipulate the data in a database • Structured Query Language (SQL): ANSI standard query language for relational databases • Database programs can produce reports, documents, and other outputs Chapter 4 – Organizing Data and Information Slide 35

  36. SQL Commands Examples of SQL Commands Chapter 4 – Organizing Data and Information Slide 36

  37. Database Administration • Database administrator (DBA): directs or performs all activities to maintain a database environment • Designing, implementing, and maintaining the database system and the DBMS • Establishing policies and procedures • Employee training Chapter 4 – Organizing Data and Information Slide 37

  38. Popular DBMS • Popular DBMSs for end users: Microsoft Access and FileMaker Pro • Entire market includes databases by IBM, Oracle, and Microsoft • Examples of open-source database systems: PostgreSQL and MySQL • Many traditional database programs are now available on open-source operating systems Chapter 4 – Organizing Data and Information Slide 38

  39. Selecting a DBMS • Important characteristics of databases to consider • Size of the database • Cost of the system • Number of concurrent users • Performance • Ability to be integrated with other systems • Vendor considerations Chapter 4 – Organizing Data and Information Slide 39

  40. Using DBMS with Other Software • DBMS are often used with other software packages or the Internet • A DBMS can act as a front-end application or a back-end application • Front-end application: interacts with users • Back-end application: interacts with applications Chapter 4 – Organizing Data and Information Slide 40

  41. Linking Databases to the Internet • Linking databases to the Internet is important for many organizations and people • Allows people to access and manipulate a number of traditional databases at the same time through the Internet Chapter 4 – Organizing Data and Information Slide 41

  42. 7. Data Warehouses and Data Marts • Data warehouse: collects business information from many sources in the enterprise • Data mart: a subset of a data warehouse Chapter 4 – Organizing Data and Information Slide 42

  43. Data mining • Data mining: an information-analysis tool for discovering patterns and relationships in a data warehouse or a data mart J. Berri Chapter3 – Binary Number System Slide 43

  44. Elements of data warehouse Elements of a Data Warehouse Chapter 4 – Organizing Data and Information Slide 44

  45. 8. Business Intelligence • Business intelligence (BI): gathering the right information in a timely manner and usable form and analyzing it to have a positive impact on business and enterprise • Turns data into useful information that is then distributed throughout an enterprise Chapter 4 – Organizing Data and Information Slide 45

  46. Business Intelligence (cont.) • Competitive intelligence: aspect of business intelligence limited to information about competitors and the ways that knowledge affects strategy, tactics, and operations • Counterintelligence: steps an organization takes to protect information sought by “hostile” intelligence gatherers Chapter 4 – Organizing Data and Information Slide 46

  47. 9. Online Analytical Processing (OLAP) • Software that allows users to explore data from a number of different perspectives Comparison of OLAP and Data Mining Chapter 4 – Organizing Data and Information Slide 47

  48. 10. Object-Oriented Databases • Object-oriented database • Stores both data and its processing instructions • Method: a procedure or action • Message: a request to execute or run a method Chapter 4 – Organizing Data and Information Slide 48

  49. 11. Summary • Hierarchy of data: bits, characters, fields, records, files, and databases • Entity: generalized class of people, places, or things for which data is collected, stored, and maintained • Attribute: characteristic of an entity • Data model: diagram of data entities and relationships • Relational model: describes data in which all elements are placed in two-dimensional tables called relations Chapter 4 – Organizing Data and Information Slide 49

  50. Summary (cont.) • A database management system (DBMS) is a group of programs used as an interface between: • Database and application programs • Database and the user • Data warehouse: database that collects business information from all aspects of a company’s processes, products, and customers • Data mining: an information-analysis tool for discovering patterns and relationships in a data warehouse Chapter 4 – Organizing Data and Information Slide 50

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