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Chapter 3 : Distributed Data Processing

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

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Chapter 3 : Distributed Data Processing

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  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

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