1. 7.1 Managing Data Resources Chapter 7 Essentials of Management Information Systems, 6e Chapter 7 Managing Data Resources © 2005 by Prentice Hall

2. 7.2 Management Challenges 1.Organizational obstacles to a database environment 2.Cost/benefit considerations

3. 7.3 Bit: Smallest unit of data; binary digit (0,1) Byte: Group of bits that represents a single character Field: Group of words or complete number Record: Group of related fields File: Group of records of the same type Organizing Data in a Traditional File Environment File Organization Terms and Concepts

4. 7.4 Database: Group of related files Entity: Person, place, thing, or event about which information must be kept Attribute: A piece of information describing a particular entity Key field: Field that uniquely identifies every record in a file Organizing Data in a Traditional File Environment File Organization Terms and Concepts

5. 7.5 Organizing Data in a Traditional File Environment The data hierarchy Figure 7-1

6. 7.6 Organizing Data in a Traditional File Environment Entities and attributes Figure 7-2

7. 7.7 Data redundancy Program-data dependence Lack of flexibility Poor security Lack of data-sharing and availability Organizing Data in a Traditional File Environment Problems with the Traditional File Environment

8. 7.8 Organizing Data in a Traditional File Environment Traditional file processing Figure 7-3

9. 7.9 Database Collection of centralized data Controls redundant data Data stored so as to appear to users in one location Services multiple application The Database Approach to Data Management Database Management Systems

10. 7.10 The Database Approach to Data Management The contemporary database environment Figure 7-4

11. 7.11 Database Management System (DBMS) Creates and maintains databases Eliminates requirement for data definition statements Acts as interface between application programs and physical data files Separates logical and physical views of data The Database Approach to Data Management Database Management Systems

12. 7.12 Three Components to a DBMS 1.Data definition language: Formal language programmers use to specify structure of database 2.Data manipulation language: For extracting data from database, e.g. SQL 3.Data dictionary: Tool for storing, organizing definitions of data elements and data characteristics The Database Approach to Data Management Database Management Systems

13. 7.13 The Database Approach to Data Management Sample data dictionary report Figure 7-5

14. 7.14 How a DBMS Solves Problems of a Traditional File Environment Reduces data redundancy Eliminates data inconsistency Uncouples programs from data Increases access and availability of data Allows central management of data, data use, and security The Database Approach to Data Management Database Management Systems

15. 7.15 Relational DBMS Represents data as two-dimensional tables called relations Relates data across tables based on common data element Examples: DB2, Oracle, MS SQL Server The Database Approach to Data Management Types of Databases

16. 7.16 The Database Approach to Data Management The relational data model Figure 7-6

17. 7.17 Three Basic Operations in a Relational Database Select: Creates subset of rows that meet specific criteria Join: Combines relational tables to provide users with information Project: Enables users to create new tables containing only relevant information The Database Approach to Data Management Types of Databases

18. 7.18 The Database Approach to Data Management The three basic operations of a relational DBMS Figure 7-7

19. 7.19 Hierarchical DBMS Older system presenting data in tree-like structure Models one-to-many parent-child relationships Found in large legacy systems requiring intensive high- volume transactions: Banks; insurance companies Examples: IBMs IMS The Database Approach to Data Management Types of Databases

20. 7.20 The Database Approach to Data Management A hierarchical database for a human resources system Figure 7-8

21. 7.21 Network DBMS Older logical database model Models many-to-many parent-child relationships Example: Student – course relationship: Each student has many courses; each course has many students The Database Approach to Data Management Types of Databases

22. 7.22 The Database Approach to Data Management The network data model Figure 7-9

23. 7.23 Disadvantages of Hierarchical and Network DBMS Outdated Less flexible compared to RDBMS Lack support for ad-hoc and English language-like queries The Database Approach to Data Management Types of Databases

24. 7.24 Object-Oriented Databases (OODBMS) Stores data and procedures as objects Better able to handle graphics and recursive data Data models more flexible Slower than RDBMS Hybrid: object-relational DBMS The Database Approach to Data Management Types of Databases

25. 7.25 Two Design Exercises in Creating Database Conceptual (logical) design: Abstract model of database from business perspective Physical design: How the database is actually arranged on direct access storage devices Creating a Database Environment Designing Databases

26. 7.26 Conceptual Database Design Identifies relationships between data elements Identifies most efficient way to group data elements Identifies redundant data elements Identifies grouping of data elements needed for specific applications Creating a Database Environment Designing Databases

27. 7.27 Entity-Relationship Diagram A methodology for documenting databases that illustrates the relationship between various elements in the database Normalization The process of creating small, stable, and adaptive data structures from complex groups of data when designing a relational database Creating a Database Environment Designing Databases

28. 7.28 Creating a Database Environment An entity-relationship diagram Figure 7-10

29. 7.29 Creating a Database Environment An unnormalized relation for ORDER Figure 7-11

30. 7.30 Creating a Database Environment A normalized relation for ORDER Figure 7-12

31. 7.31 Distributed Database Partitioned or replicated to more than one location Increases service and responsiveness Reduces vulnerability of single, massive central site Depend on telecommunication lines Pose security risks through distribution of sensitive data Central data must be updated or justified with local data Creating a Database Environment Distributing Databases

32. 7.32 Creating a Database Environment Distributed databases Figure 7-13

33. 7.33 Creating a Database Environment Key organizational elements in the database environment Figure 7-14

34. 7.34 Data Administration Develop information policy Define information requirements Plan for data Oversee logical database design and database dictionary development Monitor use of information Creating a Database Environment Management Requirements for Database Systems

35. 7.35 Data Planning and Modeling Methodology Enterprise-wide planning for data Identify key entities, attributes, and relationships that constitute the organization’s data Creating a Database Environment Management Requirements for Database Systems

36. 7.36 Database Technology, Management, and Users Databases require DBMS software and staff Database design group defines and organizes structure and content of database Database administration: establish physical database, logical relations, access rules Creating a Database Environment Management Requirements for Database Systems

37. 7.37 Online Analytical Processing (OLAP) Multidimensional data analysis Enables users to view the same data in different ways using multiple dimensions Each aspect of information – product, price, region – represents a different dimension Database Trends Multidimensional Data Analysis

38. 7.38 Database Trends Multidimensional data model Figure 7-15

39. 7.39 Data warehouse: Stores current and historical data for reporting, analysis Data mart: Subset of data warehouse with summary of data for specific users Datamining: Techniques to find hidden patterns, relationships in large pools of data to infer rules for predicting future trends Database Trends Data Warehouses and Datamining

40. 7.40 Database Trends Components of a data warehouse Figure 7-16

41. 7.41 Benefits of Data Warehouses Improved information and accessibility Ability to model and remodel data Enable access to data without affecting performance of underlying operational legacy systems Database Trends Data Warehouses and Datamining

42. 7.42 Data Reveal New Sales Opportunities How did the use of data warehouses and datamining help management at these companies make better decisions? What value do these systems provide? Database Trends Window on Management

43. 7.43 Hypermedia database Organizes data as network of nodes Links nodes in pattern specified by user Supports text, graphic, sound, video and executable programs Database Trends Data Warehouses and Datamining

44. 7.44 Database Trends A hypermedia database Figure 7-17

45. 7.45 Linking Internal Databases to the Web Database server: –Hosts DBMS –Receives SQL requests –Provides required data Middleware: –Works between Web server and DBMS to take requests –Handles connectivity to database –Can be application server or CGI scripts Database Trends Databases and the Web

46. 7.46 Database Trends Linking internal databases to the Web Figure 7-18

47. 7.47 Advantages to Web Access to Databases Browser software easy to use; little training Web interface requires no changes to internal database Costs less than custom interfaces Database Trends Databases and the Web

48. 7.48 Web Access for Royal Bank Statements Pays Off What are the business benefits of providing a Web interface for the Bankbook Reconstruct application? What value does this application provide the company and its customers? Database Trends Window on Technology