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

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
What are the disadvantages???

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. 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

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 in control of corporate information resources
Suboptimal procurement
Duplication of effort

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

9. 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)

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

11. 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

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

13. 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

14. 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