Chapter 3 : Distributed Data Processing Business Data Communications, 5e

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

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

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

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?

Benefits of DDP 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

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 in control of corporate information resources Suboptimal procurement Duplication of effort

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

Intranets Uses Internet-based standards & TCP/IP Content is accessible only to internal users A specialized form of client/server architecture Can be managed (unlike Internet)

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

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

Other forms of DDP Distributed devices Network management Example: ATM machines Network management Centralized systems provide management and control of distributed nodes

Distributed data Centralized database Replicated 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

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