1. Chapter 3 : Distributed Data Processing Business Data Communications, 4e

2. Centralized Data Processing 8Centralized computers, processing, data, control, support 8What are the advantages? 8Economies of scale (equipment and personnel) 8Lack of duplication 8Ease in enforcing standards, security

3. Distributed Data Processing 8Computers are dispersed throughout organization 8Allows greater flexibility in meeting individual needs 8More redundancy 8More autonomy

4. Why is DDP Increasing? 8Dramatically reduced workstation costs 8Improved user interfaces and desktop power 8Ability to share data across multiple servers

5. DDP Pros & Cons 8There are no “one-size-fits-all” solutions 8Key issues 8How does it affect end-users? 8How does it affect management? 8How does it affect productivity? 8How does it affect bottom-line?

6. Benefits of DDP 8Responsiveness 8Availability 8Correspondence to Org. Patterns 8Resource Sharing 8Incremental Growth 8Increased User Involvement & Control 8End-user Productivity 8Distance & location independence 8Privacy and security 8Vendor independence 8Flexibility

7. Drawbacks of DDP 8More difficulty test & failure diagnosis 8More components and dependence on communication means more points of failure 8Incompatibility of components 8Incompatibility of data 8More complex management & control 8Difficulty controlling information resources 8Suboptimal procurement 8Duplication of effort

8. Reasons for DDP 8Need for new applications 8On large centralized systems, development can take years 8On small distributed systems, development can be component-based and very fast 8Need for short response time 8Centralized systems result in contention among users and processes 8Distributed systems provide dedicated resources

9. The DP “Pendulum” 8Centralized systems (mainframes, etc) 8Distributed systems (PCs) 8Networked systems 8Client-Server computing

10. Client/Server Architecture 8Combines advantages of distributed and centralized computing 8Cost-effective, achieves economies of scale 8Flexible, scalable approach

11. Intranets 8Uses Internet-based standards & TCP/IP 8Content is accessible only to internal users 8A specialized form of client/server architecture

12. Extranets 8Similar to intranet, but provides access to controlled number of outside users 8Vendors/suppliers 8Customers

13. Distributed applications 8Horizontal partitioning 8Different applications on different systems 8One application replicated on systems 8Example: Office automation 8Vertical partitioning 8One application dispersed among systems 8Example: Retail chain POS, inventory, analysis

14. Distributed data 8Centralized database 8Pro: No duplication of data 8Con: Contention for access 8Replicated database 8Pro: No contention 8Con: High storage and data reorg/update costs 8Partitioned database 8Pro: No duplication, limited contention 8Con: Ad hoc reports more difficult to assemble

15. Networking Implications 8Connectivity requirements 8What links between components are necessary? 8Availability requirements 8Percentage of time application or data is available to users 8Performance requirements 8Response time requirements