1. Evolution of Information Technology Infrastructure and Architecture
BA Week 1 – Part 1
Sources:
HBR 397 – 118, “Intranets and Middleware”
Dr. James Coakley (Oregon State University)
MIS Textbook by Turban, Rainer & Potter (Chapter 5)
Mr. Sakthi Angappamudali (The Standard)
Mr. Lee Martin (Hitachi Consulting)
Dr. V.T. Raja (Oregon State University)

2. BA572 Week 1 (Part 1) Outline IT Infrastructure vs. IT Architecture
Evolution of IT Infrastructure and Architecture
Major eras of the computer industry
Terminology/Acronyms
Centralized/Decentralized/Distributed Computing
TPS, MIS, DSS, ES, Middleware, OOP, DW, OLAP, Data Mining etc.
Comment on Performance Metrics

3. Definitions
Information Technology (IT) Infrastructure: physical facilities, services and management that support computing resources
Information Technology
Hardware
Software
Database
Telecommunications & Networks
IT personnel

4. Definitions
Information Systems (IS) Architecture: the “plan” that aligns IT infrastructure with business needs
Help people effectively fulfill their information needs
Note that the term “Information Architecture” is also being used to describe process of designing web sites

5. Adapted from "Intranets and Middleware", HBR 397-118.

6. Evolution of Information Technology Infrastructuredb
Web Services
Distributed db db
Client/Server db
PC/LAN
Mainframe

7. Data Processing Era IT Infrastructure (host-centric processing)
Mainframe
Data Processing Era
IT Infrastructure (host-centric processing)
Hardware: Mainframe with text-based terminals
Software: Independent functional applications
Served one purpose
Data Storage: independent “files” for each functional application
Telecommunications: Limited support of distributed operations
IT Personnel: technically oriented

8. IS Architecture: Transaction Processing System (TPS)
Mainframe
IS Architecture: Transaction Processing System (TPS)
Emerged in the early days of IS
Collect, store, and process transactions
Source documents are basis for input
Perform routine, repetitive tasks
Found in all functions of an organization
If they fail, the whole organization may suffer
Automate “highly structured” decision processes
Payroll

9. IS Architecture: Management Information System (MIS)
Mainframe
IS Architecture: Management Information System (MIS)
Convert/use TPS data to support monitoring
Alert managers to problems or opportunities
Provide periodic and routine reports
e.g., summary reports, exception reports, comparison reports
Provide structured information to support decision making
Resulted in “Information overload”

10. IS Architecture: Centralized Corporate Structure
Mainframe
IS Architecture: Centralized Corporate Structure
Functional Transaction Processing System
Executive
Management Information System
Managerial
Purchasing
Sales
Inbound Logistics
Raw Materials
Production
Finished Goods
Outbound Logistics
Operational

11. Micro-Computing Era IT Infrastructure (PC environment)
PC/LAN
Micro-Computing Era
IT Infrastructure (PC environment)
Hardware: PCs (low cost compared to mainframe)
Software: Individual PC applications
Data storage: Individual files linked to apps
Telecommunications: low-speed LANs
IT Personnel: technically oriented & mainframe biased

12. IS Architecture: Decision Support Systems
PC/LAN db
IS Architecture: Decision Support Systems db db db
Proliferation of desktop applications
Why?
TPS/MIS were not providing information needed to support decisions
“End-user” development
Undocumented spreadsheet models
Proliferation of localized data storage

13. IS Architecture Executive Managerial Purchasing Sales
PC/LAN
IS Architecture
Functional Transaction Processing System
Executive
Management Information System
Desktop Decision Support System
Managerial
Purchasing
Sales
Inbound Logistics
Raw Materials
Production
Finished Goods
Outbound Logistics
Operational

14. *
Client/Server db
07/16/96
Client/Server Era
IT Infrastructure (distributed computing environment)
Hardware: PCs and Specialized Servers
Software: Facilitating
Data storage: Distributed Relational database and centralized warehouse
Telecommunications: high-speed LANs
Network: Client/Server
IT Personnel: technically skilled, business oriented
Information Systems architecture?
Share applications and data within and across functional areas *

15. Facilitating Software Systems
Client/Server db
Facilitating Software Systems
Office automation
IT for “office” employees
Document tracking, communication, scheduling, etc.

16. Facilitating Software Systems (cont’d)
Client/Server db
Facilitating Software Systems (cont’d)
Decision Support Systems
Provide information to support “semi-structured” decision making
Effectiveness focus
Expert Systems
Knowledge-base integrated with DSS
Most are “rule-based” systems that process facts, not numbers
Credit evaluation
Cisco/DELL tech support

17. Database Approaches Centralized All data in one location
Client/Server db
Database Approaches
Centralized
All data in one location
Promotes maintenance and security
Subject to single point of failure

18. Database Approaches Distributed data managementdb
Distributed
Database Approaches
Distributed data management
Get data closer to applications
Replicated
Complete copies in multiple locations
Significant overhead
Partitioned
Each location has portion of database
Data management becomes an issue
Complex Concurrency Control

19. Online Transaction Processingdb
Distributed
Online Transaction Processing
Transactions used to interact with a relational “client-server” database
For each transaction, OLTP typically deals with a small number of rows from the tables
The transactions are typically highly structured, repetitive and have predetermined outcomes
E.g., orders, changing customer address, etc.

20. Client/Server Systems
Functional Transaction Processing System
Executive db
Client/Server System
Managerial db db db db db
Purchasing
Sales
Inbound Logistics
Raw Materials
Production
Finished Goods
Outbound Logistics
Operational

21. Network Era (Distributed Computing)*
07/16/96 db
Distributed Computing
Middleware
Network Era (Distributed Computing)
IT Infrastructure (distributed computing environment)
Hardware: PCs and high-end Servers
Software: Enabling, enterprise-wide
Data storage: Distributed Relational Database
Telecommunications: high-speed WAN
Network: Middleware
IT Personnel: still technical, but business awareness *

22. Introduction of Middlewaredb
Distributed Computing
Middleware
Software that makes it possible for systems on different platforms to communicate with each other.
Allows applications to talk to each other
Consistent Application Program Interface (API)
Code application to talk to middleware, not underlying resources
Upgrade/modify underlying resources without needing to modify applications

23. Object Request Broker (ORB)db
Distributed Computing
Middleware
Object Request Broker (ORB)
ORB involves synchronous communication and location/platform transparency.
ORB uses object-oriented programming methods.

24. Distributed Computing
ORB (cont’d) db
Distributed Computing
Middleware
ORB architecture:
ORB
activate service
locate service
establish connection
Remote Service
Client
communicate

25. Distributed Computing
File Sharing db
Distributed Computing
Middleware
Napster:
ORB
activate service
locate service
establish connection
Stored Files
Request
communicate

26. Peer-to-Peer File Sharingdb
Distributed Computing
Middleware
Member
Kazaa:
Member
Member
Member
Member
Member
Request
Member
Member
Member
Member
Member
Member

27. Advantages of ORB Middlewaredb
Distributed Computing
Middleware
Anonymous interaction among applications
Integrate new client/server applications with existing legacy, mission-critical applications
Easier development environment
Reduce cost
Improve time-to-market of applications
Enables distributed data environment
Enables dynamic web applications

28. Disadvantages of ORB Middlewaredb
Distributed Computing
Middleware
Switching costs are high
Upgrade from previous “Middleware” solutions
Requires high technical expertise
Tend to outsource
Lengthy deployment time

29. Unresolved Issues with ORBdb
Distributed Computing
Middleware
Security
Scalability
Related to network capacity
Rapidly changing technologies

30. Distributed Computingdb
Distributed Computing
Middleware
DBMS Applications
With advent of high-speed, distributed architectures expanded our use of database beyond capturing and storing transaction data
Knowledge Discovery
Process of extracting useful knowledge from volumes of data
Supported by:
Massive data collection (Data Warehouse/Data Marts)
Multiprocessor computing
On-line Analytical Processing (OLAP)/Data mining

31. Distributed Computing
Data Warehouse db
Distributed Computing
Middleware
Collection of data in support of decision making process that is:
Subject-oriented: organized by entity, not application
Integrated: stored in one place, even though it originated from a variety of sources
Crosses functional boundaries of an organization
Time-variant: represents a snapshot at one point in time
Nonvolatile: data is read-only
Typically very large

32. Data Warehouse *
07/16/96
Large repository of detailed and summary data used to support the strategic decision making process for the enterprise
Stores current and historical data (internal and external)
Integrates data from organization’s disparate information systems used by functional units
Involve hundreds of gigabytes, and terabytes of data
Run on very powerful computers
Expensive *

33. Data Warehousing Process
OLTP - Raw Detail
No/Minimal History
DW-Integrated
Scrubbed
History
Summaries
Targeted
Specialized (OLAP)
OLTP, DW and DM - Data Characteristics
Design
Mapping
OLTP
Systems
Functional IS
External
Data
Data Mart
Central
Repository
Load
Index
Aggregation
Data
Warehouse
Extract
Scrub
Transform
End User
Workstations
Replication
Data Set Distribution

34. Multidimensional Database (cont’d)db
Distributed Computing
Middleware
Multidimensional Database (cont’d)
Data marts
Scaled-down version of a data warehouse that focuses on a specific area
e.g., a department, a business process

35. An Incremental Approach
Sales
Distribution
Product
Glossary
Customer
Marketing
Accounts
Common Business
Metrics
Common Business Rules
Operations
and Inventory
Finance
Vendors
Common Business Dimensions
Common Logical Subject Area ERD
Individual Architected Data Marts

36. The Eventual Result Architected Enterprise Foundation
Sales
Distribution
Product
Marketing
Customer
Accounts
Finance
Operations
and Inventory
Vendors
Enterprise Data Warehouse
Architected
Enterprise
Foundation

37. Multidimensional Databasedb
Distributed Computing
Middleware
Multidimensional Database
OLTP not good when doing analysis of data – poor performance
OLAP – on-line analytical processing

38. *
07/16/96
On-line Transaction Processing (OLTP) and On-line Analytical Processing (OLAP)
OLTP: Immediate processing/analysis and handling of multiple concurrent transactions from customers/users
Example:
OLAP: Capability for manipulating and analyzing large volumes of data from multiple perspectives (multidimensional analysis)
OLTP – Example: B-C E-Commerce (Amazon.com)
OLAP – Example: Product vs. Region vs. Sales *

39. “Slice and Dice” an OLAP Cube

40. Distributed Computingdb
Distributed Computing
Middleware
Advantages of OLAP
All hierarchical or aggregated values can be pre-calculated in the cube rather than accessing the Warehouse
Major reduction in query time
Each cube makes “business sense”
Not normalized data structures

41. Distributed Computingdb
Distributed Computing
Middleware
Massive Data Analysis
Data mining
Provides a means to extract patterns and relationships
Example: Analyze sales data to identify products that may be attractive to a customer
Amazon.com buyer suggestions
Two capabilities
Automated prediction of trends and behaviors
Automated discovery of previously unknown patterns

42. Data Mining Some Benefits: Market Segmentation Fraud Detection*
07/16/96
Data Mining
Some Benefits:
Market Segmentation
Fraud Detection
Market Basket Analysis
Trend Analysis
Market Segmentation: Identify common characteristics of customers who purchase the same products
Fraud Detection: Identify which transactions are most likely to be fraudulent
Market Basket Analysis: Understanding what products/services are commonly purchased together (e.g, Beer/Diapers)
Trend Analysis: Reveals the difference between a typical customer this year versus last year *

43. Business Intelligence
BI/Analytics software (suite):
Used to collect, store, analyze and present
sufficient and accurate information in a timely manner and in a usable form
Includes OLAP, data mining, statistical analysis
Has a positive impact on business strategy, and operations
Addresses analysis paralysis caused due to information overload?

44. Business Intelligence
Enterprise BI Suites and Platforms

45. The Decision Making Roadmap
Business Planning
Actions
Vision
Knowledge
Transaction
Systems
Decision
Support
Systems
Executive
Information
Systems?
Data
Information
RUN
MANAGE
GROW
Operational
Functional
Current
Detailed
Analyze What If Scenarios
History
Detailed
Multi-Dimensional
History
Summary
Users
Knowledge Brokers
Management

46. Network Enabling Softwaredb
Distributed Computing
Middleware
Network Enabling Software
Supply Chain Management
Customer Relationship Management
Enterprise Wide Systems
Enterprise Wide Systems
Enterprise Wide Systems
Supplier
Customer

47. Internet Era IT Infrastructure (Web-enabled)*
Internet Era
07/16/96
IT Infrastructure (Web-enabled)
Hardware: Low-end PC with Browser, high-end Servers
Software: Web extensions
Database: Distributed Relational
Network: Use IP-based standards
Telecommunications: broadband
IT Personnel: Business analysts, technical specialties *

48. Business use of the Internet: Electronic Commerce
B2C: Internet
B2B: Extranet
B2E: Intranet
E-business:
Subset of e-commerce
Transactions between business partners
Enterprise
Supplier/ Customer
Individual
Extranet
Internet
Intranet

49. Web-based Solutions
Early attempts to incorporate WWW into inter-organizational systems
Static, state-less web pages
Complicated navigation
Not “connected” to underlying data
Page not dynamically updated when data changes
Dynamic and interactive web applications connected to enterprise database(s)
Web 2.0

50. Web Services Standards are evolving Security?db
Web Services
Web Services
Standards are evolving
Security?
Do web services 'solve' interoperability between applications?
Need ERP?

51. Comment on Performance Metrics*
Comment on Performance Metrics
07/16/96
How does IT add value and how much value?
TCO/ROI
Tangible vs. Intangible Impacts
What is(are) purpose(s) of IT applications?
Automate
Facilitate/Informate
Enable business strategy/significant competitive advantage
Alignment of IT and Business Strategy
“ROI”? *