1. 6.1 © 2007 by Prentice Hall 6 Chapter Foundations of Business Intelligence: Databases and Information Management

2. 6.2 © 2007 by Prentice Hall LEARNING OBJECTIVES Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Describe basic file organization concepts and the problems of managing data resources in a traditional file environment. Describe the principles of a database management system and the features of a relational database. Apply important database design principles.

3. 6.3 © 2007 by Prentice Hall LEARNING OBJECTIVES (cont’d) Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Evaluate tools and technologies for providing information from databases to improve business performance and decision making. Assess the role of information policy, data administration, and data quality assurance in the management of organizational data resources.

4. 6.4 © 2007 by Prentice Hall Nascar Races to Manage Its Data Problem: Gaining knowledge of customers and making effective use of fragmented customer data. Solutions: Use relational database technology to increase revenue and productivity. Data access rules and a comprehensive customer database consolidate customer data. Demonstrates IT’s role in creating customer intimacy and stabilizing infrastructure. Illustrates digital technology’s role in standardizing how data from disparate sources are stored, organized, and managed. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

5. 6.5 © 2007 by Prentice Hall Organizing Data in a Traditional File Environment File organization concepts Problems with the traditional file environment Data redundancy and inconsistency Program-data dependence Lack of flexibility Poor security Lack of data sharing and availability Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

6. 6.6 © 2007 by Prentice Hall Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

7. 6.7 © 2007 by Prentice Hall Traditional File Processing Figure 6-2 The use of a traditional approach to file processing encourages each functional area in a corporation to develop specialized applications and files. Each application requires a unique data file that is likely to be a subset of the master file. These subsets of the master file lead to data redundancy and inconsistency, processing inflexibility, and wasted storage resources. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Organizing Data in a Traditional File Environment

8. 6.8 © 2007 by Prentice Hall Data Redundancy & Inconsistency Data redundancy : the presence of duplicate data in multiple data files so that the same data are stored in more than place or location. Data redundancy occurs when different groups in an organization independently collect the same piece of data and store it independently of each other. Data inconsistency: the same attribute may have different values. Problems with the Traditional File Environment Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

9. 6.9 © 2007 by Prentice Hall Program-Data Dependence The coupling of data stored in files and the specific programs required to update and maintain those files such that changes in programs require changes to the data. E.g : change from a five-digit to a nine-digit ZIP code. Poor security Because there is little control or management of data, access to and dissemination of information may be out of control. Problems with the Traditional File Environment Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

10. 6.10 © 2007 by Prentice Hall Lack of Flexibility Can deliver routine reports after extensive programming efforts. Cannot deliver ad hoc report or respond to unanticipated information requirements in a timely fashion. Lack of data sharing and availability It is virtually impossible for information to be shared or accessed in a timely manner. Information cannot flow freely across different functional areas or different parts of the organization. If users find different values of the same piece of information in two different systems, they may not want to use these systems because they cannot trust the accuracy of their data. Problems with the Traditional File Environment Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

11. 6.11 © 2007 by Prentice Hall Database management systems How a DBMS solves the problems of the traditional file environment Relational DBMS Operations of a relational DBMS Object-oriented DBMS The Database Approach to Data Management Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

12. 6.12 © 2007 by Prentice Hall Database management systems How a DBMS solves the problems of the traditional file environment DBMS reduce data redundancy and inconsistency by minimizing isolated files in which the same data are repeated. DBMS uncouples programs and data, enabling data to stand on their own. DBMS enables the organization to centrally manage data, their use, and security. The Database Approach to Data Management Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

13. 6.13 © 2007 by Prentice Hall The Database Approach to Data Management Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Figure 6-3 A single human resources database provides many different views of data, depending on the information requirements of the user. Illustrated here are two possible views, one of interest to a benefits specialist and one of interest to a member of the company’s payroll department. Human Resources Database with Multiple Views

14. 6.14 © 2007 by Prentice Hall The Database Approach to Data Management Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Figure 6-4

15. 6.15 © 2007 by Prentice Hall The Database Approach to Data Management Relational DBMS Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Customer TableOrder Table Field Name DescriptionField NameDescription Customer Name Self- Explanatory Order Number Primary Key Customer Address Self- Explanatory Order ItemSelf- Explanatory Customer IDPrimary KeyNumber of Items Ordered Self- Explanatory Order Number Secondary KeyCustomer IDSecondary Key

16. 6.16 © 2007 by Prentice Hall The Database Approach to Data Management Operations of relational DBMS Figure 6-5 Object-oriented DBMS Stores the data and procedures that act on those data as objects that can be automatically retrieved and shared. Suitable for handling graphics or multimedia applications. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

17. 6.17 © 2007 by Prentice Hall The Database Approach to Data Management Capabilities of database management systems Querying and reporting Designing databases Normalization and entity-relationship diagrams Distributing databases Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

18. 6.18 © 2007 by Prentice Hall Distributed Databases Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Distributed database: one that is stored in more than one physical location. Benefits of distributed systems: Reduce the vulnerability of a single, massive central site. Increase service and responsiveness to local users and often can run on smaller, less expensive computers.

19. 6.19 © 2007 by Prentice Hall Distributed Databases Figure 6-12 There are alternative ways of distributing a database. The central database can be partitioned (a) so that each remote processor has the necessary data to serve its own local needs. The central database also can be replicated (b) at all remote locations. The Database Approach to Data Management Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

20. 6.20 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Database warehouses What is a data warehouse? Data marts Online analytical processing (OLAP) Data mining Databases and the Web

21. 6.21 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Database warehouses What is a data warehouse? Database that stores current and historical data of potential interest to decision makers throughout the company. Data marts Is a subset of a data warehouse in which a summarized or highly focused portion of the organization’s data is placed in a separate database for specific population of users.

22. 6.22 © 2007 by Prentice Hall Components of a Data Warehouse Figure 6-13 The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined with data from external sources and reorganized into a central database designed for management reporting and analysis. The information directory provides users with information about the data available in the warehouse. Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

23. 6.23 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Business intelligence A series of tools enables users to analyze data to see new patterns, relationships, and insights that are useful for guiding decision making. The principal tools are: Software for database querying & reporting Software for multidimensional data analysis (OLAP) Data mining

24. 6.24 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Figure 6-14 Business Intelligence

25. 6.25 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Figure 6-15 Multidimensional Data Model

26. 6.26 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Data mining More discovery-driven Data mining provides insights into corporate data that can be obtained with OLAP by finding hidden patterns and relationships in large databases and inferring rules from them to predict future behavior. Types of information obtainable from data mining Associations Sequences Classification Clustering Forecasting

27. 6.27 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Types of information obtainable from data mining Associations are occurrences linked to a single event. Eg. A study of supermarket purchasing patterns might reveal that, when corn chips are purchased, a cola drink is purchased 65% of the time, but when there is a promotion, cola is purchased 85% of the time. In sequences, events are linked over time. Eg. That if a house is purchased, a new refrigerator will be purchased within two weeks 65% of the time, and an oven will be bought within one month of the home purchase 45% of the time.

28. 6.28 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Types of information obtainable from data mining Classification recognizes patterns that describe the group to which an item belongs by examining existing items that have been classified and by inferring a set of rules. Eg. Classification helps discover the characteristics of credit card customers who are likely to leave and can provide a model to help managers predict who those customers are so that managers can devise special campaigns to retain such customers. Clustering works in a manner to classification when no groups have yet been defined. Eg. Finding affinity groups for bank cards or partitioning a database into groups of customers based on demographics and types of personal investments.

29. 6.29 © 2007 by Prentice Hall Using Databases to Improve Business Performance and Decision Making Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Types of information obtainable from data mining Forecasting uses predictions in a different ways. It uses a series of existing values to forecast what other values will be. Eg. Forecasting might find patterns in data to helps managers estimate the future value of continuous variables, such as sales figures.

30. 6.30 © 2007 by Prentice Hall Managing Data Resources Establishing and information policy Information policy: the organization’s rules for sharing, disseminating, acquiring, standardizing, classifying, and inventorying information. Ensuring data quality Data quality audit: a structured survey of accuracy and level of completeness of the data in IS. Data cleansing: data scrubbing, consists of activities of detecting and correcting data in a database that are incorrect, incomplete, improperly formatted, or redundant. Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management

31. 6.31 © 2007 by Prentice Hall Read the Interactive Session: Management, and then discuss the following questions: What are the benefits of DNA databases? What problems do DNA databases pose? Who should be included in a national DNA database? Should it be limited to convicted felons? Explain your answer. Who should be able to use DNA databases? DNA Databases: Crime-Fighting Weapon or Threat to Privacy? Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management Using Databases to Improve Business Performance and Decision Making

32. 6.32 © 2007 by Prentice Hall Read the Interactive Session: Management, and then discuss the following questions: What was the impact of data quality problems on the companies described in this case study? What management, organization, and technology factors caused these problems? How did the companies described in this case solve their data quality problems? What management, organization, and technology issues had to be addressed? It has been said that the biggest obstacle to improving data quality is that business managers view data quality as a technical problem. Discuss how this statement applies to the companies described in this case study. What Can Be Done About Data Quality? Managing Data Resources Management Information Systems Chapter 6 Foundations of Business Intelligence: Databases and Information Management