1. Chapter 31 Information Technology For Management 6 th Edition Turban, Leidner, McLean, Wetherbe Lecture Slides by L. Beaubien, Providence College John Wiley & Sons, Inc. Data Management: Data, Databases and Warehousing

2. Chapter 32 Data Management Difficulties with managing data Solutions to managing data  Describe DBMS  Describe Data Warehousing and Analytical Processing

3. Chapter 33 The Traditional Approach To Data Management

4. Chapter 34 Databases A database is an organized logical grouping of related files. Centralized databases - all the related files are located in one physical location Distributed database  Replicated database  Partitioned database Considerations  Failure  Access speed  Maintaining consistency  Security

5. Chapter 35 The Database Approach to Data Management- Database Management Systems (DBMS)

6. Chapter 36 Advantages of DBMS Query ability (two types) Concurrency Backup and replication Rule enforcement Security Computation

7. Chapter 37 DBMS (cont’d) DBMS provides the ability for many users to share and process data by providing twoviews of the database  Physical view  Logical view DBMS Languages  DDL  DML

8. Chapter 38 Data Life Cycle Process

9. Chapter 39 Transactional vs. Analytical Data Processing Transactional processing takes place in operational systems (TPS) that provide the organization with the capability to perform business transactions and produce transaction reports. The data are organized mainly in a hierarchical structure and are centrally processed. This is done primarily for fast and efficient processing of routine, repetitive data. Supplementary activity to transaction processing is called analytical processing, which involves the analysis of accumulated data. Analytical processing, sometimes referred to as business intelligence, includes data mining, decision support systems (DSS), querying, and other analysis activities. These analyses place strategic information in the hands of decision makers to enhance productivity and make better decisions, leading to greater competitive advantage.

10. Chapter 310 Forms for Modeling Data (ERD) Business Processes Entities (for which data is collected) Attributes (characteristics of an entity) Relations

11. 11 Relational Models Describe data using a standard tabular format with all data elements placed in two-dimensional tables.

12. Chapter 312 Hierarchy of Data

13. Chapter 313 The Hierarchy of Data

14. Chapter 314 Advantages of the Database Approach

15. Chapter 315 Data Modeling Key Considerations Content – What data should be collected, and at what cost? Access – What data should be provided to which users and when? Logical structure – How should data be arranged so it makes sense to a given user? Physical organization – Where should data be physically located?

16. Chapter 316 Data Warehouse DW is a repository of data that are organized to be readily acceptable for analytical processing activities (DSS, querying, data mining) Organization Standardization of data Relational Delivery of DWH content to users on the intranet and extranet (online banking) Not all data are necessarily transferred to data warehouse Three tier vs two tier architecture

17. Chapter 317 The Data Warehouse & Data Management

18. Chapter 318 Web-based Data Management Systems – content and information

19. Chapter 319 Data warehousing is most appropriate when  Large amounts of data to be accessed  The operational data is stored i different systems  Large number of users (AT&T)  Extensive end-user computing

20. Chapter 320 Datamarts The high cost o DWH confines their use to large companies A datamart is a small warehouse designed for a department Two types  Dependent  Standalone