Chapter 8 Data and Knowledge Management

1. Chapter 8Data and Knowledge Management

2. Learning Objectives • When you finish this chapter, you will • Know the difference between traditional file organization methods and the database approach. • Know how database management systems are used to construct databases, populate them with data, and manipulate the data to produce information. • Be familiar with the different database models and the advantages and disadvantages of each model.

3. Learning Objectives • Know the most important features and operations of a relational database. • Understand how databases are changing business operations across industries and what impact they might have on our personal lives. • Understand the concepts of data warehousing and data-mining and their use in business. • Recognize the need for knowledge storage and management and be able to give examples of the ways knowledge is managed in organizations.

4. Managing Digital Data • The Traditional File Approach • Disadvantages • Program/Data Dependency • Data Redundancy • Data Integrity • Moving to Databases • Database Management System (DBMS) • Queries: Request data from specified fields • Security: Giving users different views addresses security issue

5. Figure 8.1 The layout of a personnel file in traditional file organization. Managing Digital Data

6. Figure 8.2 Different information making up a student record retained in three different sites. Managing Digital Data

7. Figure 8.3 Data hierarchy Managing Digital Data

8. Figure 8.4 Different database views reveal different combinations of data Managing Digital Data

9. Figure 8.5 Different views of one employee database Managing Digital Data

10. Managing Digital Data • Traditional Files vs. Databases: Pros and Cons • Traditional File Advantages • Simplicity • Efficiency • Customization • Database Advantages • Reduced data redundancy • Application/data independence • Better control • Flexibility

11. Figure 8.6 Advantages and disadvantages of database models Database Models

12. Database Models • The Hierarchical Model • Records are related hierarchically -- each category is a subcategory of the next level up • Disadvantages of hierarchical databases • To retrieve a record, a user must start at the root and navigate the hierarchy. • If a link is broken, the entire branch is lost. • Requires considerable data redundancy because child records can have only one parent

13. Figure 8.7 A schematic diagram of a hierarchical database (a) and a sample part of a hierarchical database showing relationships among different records (b) Database Models

14. Database Models • The Network Model • Allows a record to be linked to more than one parent • Supports many-to-many (N:M) relationships • Advantage of the network model • Reduced data redundancy • Disadvantages of the network model • Complicated to build and difficult to maintain • Difficult to navigate

15. Figure 8.8 A schematic diagram of a network database (a) and a sample of part of a network database showing relationships among different records (b) Database Models

16. Database Models • The Relational Model • Consists of tables; links among entities are maintained with foreign keys • Advantages of relational databases • Same advantages of a network database without the complications. • Easier to conceptualize and maintain. • Virtually all DBMSs offered for microcomputers accommodate the relational model.

17. Figure 8.9 A schematic diagram of a relational database (a) and a sample part of a relational database showing different tables (b) Database Models

18. Database Models • Keys • Fields whose values identify records for display or processing. • Primary key • Uniquely identifies a record • Linking

19. Database Models • The Object-Oriented Structure • Affords maintenance of data along with the applications that process them • Entity-Relationship Diagrams • Conceptual blueprint of a database • Graphical representation of all entity relationships

20. Figure 8.10 An entity-relationship diagram Database Models

21. Components of Database Management Systems • The Schema • Describes the structure of the database • The Data Dictionary (Metadata) • Maintains all information supplied by the developer when constructing the schema

22. Figure 8.12 A typical data dictionary for a staff file Components of Database Management Systems

23. Figure 8.13 Data definition language to create a schema in NOMAD Components of Database Management Systems • Data Definition Language (DDL) • Used to construct the schema

24. Figure 8.14 A Paradox query by example Components of Database Management Systems • Data Manipulation Language (DML) • Used to query the database

25. Relational Operations • Data Manipulation • Select, Project, Join • Structured Query Language (SQL) • International standard DDL and DML for relational DBMS. • Advantages of using SQL • Users do not need to learn different DDLs and DMLs. • SQL can be embedded in widely used 3rd generation languages, increasing efficiency and effectiveness. • Programmer not forced to rewrite statements since SQL statements are portable.

26. Figure 8.15 A join table of professors and their students Relational Operations

27. Figure 8.16 Popular DBMSs Popular Database Management Systems

28. Database Architecture • Distributed Databases • Replication • Full copy of the entire database is stored at all sites • Fragmentation • Parts of database are stored where they are most often accessed

29. Figure 8.17 A replicated database: each computer holds a copy of the entire database Database Architecture

30. Figure 8.18 A fragmented database: each computer holds only the part of the database that is most frequently accessed by the local users Database Architecture

31. Database Architecture • Shared Resource and Client/Server Systems • Four basic client/server models • Applications run at a server • Applications run on local PCs • Applications run on both the local PCs and the server • Applications and key elements of the database are split between the PCs and the server

32. Figure 8.19 Shared resource and client/server architectures Database Architecture

33. Web Databases • Databases on the Web • Catalogs • Libraries • Directories • Client lists and profiles • When linking a database to the Internet, consider • Which application to use • How to ensure Web surfers do not interfere with database updates • How to maintain security

34. Data Warehousing • Data warehouse • Collection of data that supports management decision making • Phases in Building a Data Warehouse • Extraction Phase • Cleansing Phase • Loading Phase • Data Mining • Selecting, exploring, and modeling data to discover unknown relationships

35. Figure 8.20 Data are warehoused for analysis and reporting Data Warehousing

36. Figure 8.21 Potential applications of data-mining Data-Mining

37. Knowledge Management • The attempt by organizations to: • Transfer knowledge into databases • Filter and separate the most relevant knowledge • Organize knowledge in databases that either • Allow other employees to easily access the knowledge • “Push” specific knowledge to employees based on their prespecified needs

38. Ethical and Societal IssuesA Too-Risky Info Highway • Out of Hand -- Out of Control • DBMSs allow organizations to collect, maintain, and sell vast amounts of private personal data easily. • Where is the Information Going? • Many consumers provide information daily without being aware of where it is actually going.

39. Ethical and Societal IssuesA Too-Risky Info Highway • Personal Data Matched, Sliced , and Diced • Pieces of personal data may be matched and put together to reveal private life in unexpected ways. • Error Propagation • In case of errors, it may be impossible to trace your data to all organizations that have it. • The Upside • Database technology enables better and faster services.