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Ppt: Chapter Three

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  • 1. Fundamentals of Information Systems Fourth Edition Chapter 3 Organizing Data and Information Edited for AK ITEC 1010 Fall, 2007
  • 2. Principles and Learning Objectives
    • See List on Page 108 of text.
    • Learn acronyms in chapter
  • 3. Why Learn About Database Systems?
    • Database systems can process and organize large amounts of data
    • Can be manual or computerized. Examples?
    • Examples
      • Marketing manager can access customer data
      • Corporate lawyer can access past cases and opinions
    P 110 Database Concept: A technology for organizing and using data.
  • 4. Introduction
    • Database: an organized collection of data
    • Database management system (DBMS): group of programs to manage database
      • Manipulates database
      • Provides an interface between database and the user of the database and other application programs
    • Database administrator (DBA): skilled IS professional who directs all activities related to an organization’s database
    The star means you really should learn this material!
  • 5. The Hierarchy of Data
    • Bit (a binary digit) : representation of on or off state
    • Byte: eight bits
    • Character: basic building block of information
      • Each byte represents a character (ASCII Standard)
      • ( In Unicode, TWO bytes = character )
      • Can be an uppercase letter, lowercase letter, numeric digit, or special symbol
    • Field: typically a name, number, or combination of characters that describes something
    P 111
  • 6. The Hierarchy of Data (continued)
    • Record: a collection of (related) data fields
    • File: a collection of related records
    • Table: Functionally equivalent with file.
    • Database: a collection of integrated and related files
    • Hierarchy of data: bits, characters, fields, records, files, and databases
  • 7. The Hierarchy of Data (continued) Figure 3.1: The Hierarchy of Data
  • 8. Data Entities, Attributes, and Keys
    • Entity: a generalized class of people, places, or things (objects) for which data is collected, stored, and maintained
    • Attribute: characteristic of an entity
    • Data item: value of an attribute
    • Key: field or set of fields in a record that is used to identify the record
    • Primary key: field or set of fields that uniquely identifies the record
  • 9. Data Entities, Attributes, and Keys (continued) Figure 3.2: Keys and Attributes
  • 10. The Database Approach
    • Traditional approach to database management: separate data files are created for each application
      • Results in data redundancy (duplication)
      • Data redundancy conflicts with data integrity
    • Database approach to database management: pool of related data is shared by multiple applications
      • Significant advantages over traditional approach
  • 11. The Database Approach (continued) Figure 3.3: The Database Approach to Data Management
  • 12. LEARN !! Tables 31. and 3.2 on page 114 Advantages and disadvantages of Database Approach
  • 13. Data Modeling and the Relational Database Model
    • 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?
  • 14. Data Modeling
    • 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
  • 15. Data Modeling (continued)
    • 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
    AK ITEC 2010.3 Covers this in much more detail. Have you considered registering yet?
  • 16. Data Modeling (continued) Figure 3.4: An Entity-Relationship (ER) Diagram for a Customer Order Database
  • 17. The Relational Database Model
    • Relational model: all data elements are placed in two-dimensional tables (relations), which are the logical equivalent of files
    • In the relational model
      • Each row of a table represents a data entity
      • ( functionally the same as a record )
      • Columns of the table represent attributes
      • Domain: the allowable values for data attributes
    P116
  • 18. The Relational Database Model (continued) Figure 3.5: A Relational Database Model Note: In Canada, SSN is called the SIN. It is not legal to require it to be used for identification, except as permitted by law, which is generally limited to identification for the federal or provincial government.
  • 19. 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
    Great Exam Questions, eh?
  • 20. Manipulating Data (continued) Figure 3.6: A Simplified ER Diagram Showing the Relationship Between the Manager, Department, and Project Tables
  • 21. Manipulating Data (continued) Figure 3.7: Linking Data Tables to Answer an Inquiry
  • 22. Database Management Systems (DBMS)
    • Interface between:
      • Database and application programs
      • Database and the user
    • Creating and implementing the right database system ensures that the database will support both business activities and goals
    • DBMS: a group of programs used as an interface between a database and application programs or a database and the user
    Definition !!
  • 23. Overview of Database Types
    • Flat file
      • Simple database program whose records (might ) have no relationship to one another
    • 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
  • 24. Providing a User View
    • 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
  • 25. Creating and Modifying the Database
    • Data definition language (DDL)
      • Collection of instructions/commands that define and describe data and data relationships in a database
      • Allows database creator to describe the data and the data relationships that are to be contained in the schema
    • Data dictionary: a detailed description of all the data used in the database
  • 26. Creating and Modifying the Database (continued) Figure 3.10: Using a Data Definition Language to Define a Schema
  • 27. Creating and Modifying the Database (continued) Figure 3.11: A Typical Data Dictionary Entry
  • 28. 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
  • 29. 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
  • 30. Manipulating Data and Generating Reports (continued) Table 3.3: Examples of SQL Commands
  • 31. 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
  • 32. Popular Database Management Systems
    • 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
  • 33. Special-Purpose Database Systems
    • Specialized database packages are used for specific purposes or in specific industries
      • Israeli Holocaust Database
      • Hazmat database
      • Art and Antique Organizer Deluxe
      • Mormon Geneology database
    • Special-purpose database by Tableau can be used to store and process visual images
    P 127
  • 34. Selecting a Database Management System
    • 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
  • 35. Using Databases with Other Software
    • Database management systems are often used with other software packages or the Internet
    • A database management system can act as a front-end application or a back-end application
      • Front-end application: interacts with users
      • Back-end application: interacts with applications
  • 36. Linking Databases to the Internet
    • Linking databases to the Internet is important for many organizations and people
    • Semantic Web
      • Developing a seamless integration of traditional databases with the Internet
      • Allows people to access and manipulate a number of traditional databases at the same time through the Internet
    Mandatory: Read This section on page 129. Study.
  • 37. Data Warehouses, Data Marts, and Data Mining
    • Data warehouse: collects business information from many sources in the enterprise
    • Data mart: a subset of a data warehouse
    • Data mining: an information-analysis tool for discovering patterns and relationships in a data warehouse or a data mart
    Page 129: Study details
  • 38. Data Warehouses, Data Marts, and Data Mining (continued) Figure 3.17: Elements of a Data Warehouse
  • 39. Data Warehouses, Data Marts, and Data Mining (continued) Table 3.5: Common Data-Mining Applications
  • 40. 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
      • Turns data into useful information that is then distributed throughout an enterprise
  • 41. Business Intelligence (continued)
    • 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
    Page 135: Study details
  • 42. Distributed Databases
    • Distributed database
      • Data may be spread across several smaller databases connected via telecommunications devices
      • Corporations get more flexibility in how databases are organized and used
    • Replicated database
      • Holds a duplicate set of frequently used data
    Page 129: Study details
  • 43. Online Analytical Processing (OLAP)
    • Software that allows users to explore data from a number of different perspectives
    Table 3.6: Comparison of OLAP and Data Mining
  • 44. Object-Oriented and Object-Relational Database Management Systems
    • Object-oriented database
      • Stores both data and its processing instructions
      • Method: a procedure or action
      • Message: a request to execute or run a method
    Page 129: Study details
  • 45. Object-Oriented and Object-Relational Database Management Systems (continued)
    • Object-oriented database management system (OODBMS)
      • Programs that manipulate an object-oriented database and provide a user interface and connections to other application programs
    • Object-relational database management system (ORDBMS)
      • A DBMS capable of manipulating audio, video, and graphical data
  • 46. Visual, Audio, and Other Database Systems
    • Visual databases for storing images
    • Audio databases for storing sound
    • Virtual database systems: allow different databases to work together as a unified database system
    • Other special-purpose database systems
      • Spatial data technology: stores and accesses data according to the locations it describes and permits spatial queries and analysis
  • 47. Summary
    • Hierarchy of data: bits, characters, fields, records, files, and databases
    • Entity: generalized class of people, places, or things (objects) 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
  • 48. Summary (continued)
    • Selecting: eliminates rows according to criteria
    • Projecting: eliminates columns in a table
    • A database management system (DBMS) is a group of programs used as an interface between:
      • Database and application programs
      • Database and the user
    • Data dictionary: detailed description of all the data used in the database
  • 49. Summary (continued)
    • 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
    • Object-oriented database: stores both data and its processing instructions
  • 50. END Right Here! Same Place !! More Excitement Next week !!!

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