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

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

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

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

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

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

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

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

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

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

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

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

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

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

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