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DefinitionsInformation Technology (IT) Infrastructure:
physical facilities, services and management
that support computing resources Information Technology
Hardware
SoftwareDatabase
Telecommunications & Networks
IT personnel
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DefinitionsInformation Systems (IS) Architecture: the
“plan” that aligns IT infrastructure with
business needsHelp people effectively fulfill their information
needs
Note that the term “Information Architecture” isnow being used to describe process of designing
web sites
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Performance Metrics
“ROI” How does IT add value?
What is purpose of IT applications?Automate
Facilitate/Informate
Enable
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Adapted from "Intranets and Middleware", HBR 397-118.
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S1
19601980
1990
A b i l i t y t o f i
l l i n f o r m a t i o n n e e d s
2000
PC/LAN
Client/Server db
db
db
Distributed
db
dbdb dbdb
Web Services
Mainframe
Evolution of Information Technology Infrastructure
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Data Processing EraIT Infrastructure (host-centric processing)Hardware: Mainframe with text-based terminals
Software: Independent functional applicationsServed one purpose
Data Storage: independent “files” for each
functional applicationTelecommunications: Limited support of
distributed operations
IT Personnel: technically oriented
Mainframe
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IS Architecture:
Transaction Processing System (TPS)Emerged in the early days of ISCollect, 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 sufferAutomate “highly structured” decision processes
Payroll
Mainframe
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IS Architecture:
Management Information System (MIS)Convert/use TPS data to support monitoringAlert managers to problems or opportunities
Provide periodic and routine reportse.g., summary reports, exception reports, comparison
reports
Provide structured information to support decision
makingResulted in “Information overload”
Mainframe
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IS Architecture:Centralized Corporate Structure
Executive
Operational
Managerial
Inbound
Logistics
Purchasing
Raw
Materials
Production Finished
Goods
Outbound
Logistics
Sales
Functional Transaction
Processing System
Management
Information System
Mainframe
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Micro-Computing EraIT Infrastructure (PC environment)Hardware: PCs (low cost compared to mainframe)
Software: Individual PC applicationsData storage: Individual files linked to apps
Telecommunications: low-speed LANs
IT Personnel: technically oriented & mainframe biased
PC/LAN
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IS Architecture:
Decision Support SystemsProliferation of desktop applicationsWhy?
TPS/MIS were not providing information needed tosupport decisions
“End-user” development Undocumented spreadsheet models
Proliferation of localized data storage
PC/LAN
db
db
db
db
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IS Architecture
Executive
Operational
Managerial
Inbound
Logistics
Purchasing
Raw
Materials
Production Finished
Goods
Outbound
Logistics
Sales
Functional Transaction
Processing System
Management
Information System
Desktop Decision
Support System
PC/LAN
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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
Client/Server
db
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Facilitating Software Systems Office automation IT for “office” employees
Document tracking, communication, scheduling, etc.
Client/Server
db
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Facilitating Software Systems
(cont’d) Decision Support Systems
Provide information to support “semi-structured”
decision makingEffectiveness focus
Expert SystemsKnowledge-base integrated with DSS
Most are “rule- based” systems that process facts, notnumbersCredit evaluation
Cisco/DELL tech support
Client/Server
db
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Di ib d
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Database ApproachesDistributed data managementGet data closer to applications
ReplicatedComplete copies in multiple locations
Significant overhead
PartitionedEach location has portion of database
Data management becomes an issue Complex Concurrency Control
db
db
db
Distributed
db
db
Di t ib t d
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Transactions used to interact with a relational“client-server” database For each transaction, OLTP typically deals with
a small number of rows from the tablesThe transactions are typically highly
structured, repetitive and have predeterminedoutcomes
E.g., orders, changing customer address, etc.
Online Transaction
Processing
db
db
db
Distributed
db
db
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Client/Server Systems
Executive
Operational
Managerial
Inbound
Logistics
Purchasing
Raw
Materials
Production Finished
Goods
Outbound
Logistics
Sales
Functional Transaction
Processing System
Client/Server
System
db db db db db
db
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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
db dbdbdb
Distributed Computing
Middleware
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Introduction of
Middleware
Software that makes it possible for systems on
different platforms to communicate with eachother.Allows applications to talk to each other
Consistent Application Program Interface (API)
Code application to talk to middleware, not underlyingresources
Upgrade/modify underlying resources without needingto modify applications
db dbdbdb
Distributed Computing
Middleware
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Object Request Broker(ORB)
ORB involves synchronous communication
and location/platform transparency.
ORB uses object-oriented programming
methods.
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Distributed Computing
Middleware
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ORB (cont’d)
ORB architecture:
ORB
ClientRemote Service
locate
service
activate
service
establish connection
communicate
db dbdbdb
Distributed Computing
Middleware
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File Sharing
Napster:
ORB
RequestStored Files
locate
service
activate
service
establish connection
communicate
db dbdbdb
Distributed Computing
Middleware
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Peer-to-PeerFile Sharing
Kazaa:
Request
Member
Member
Member
Member
MemberMember
Member
MemberMember
Member
Member
Member
db dbdbdb
Distributed Computing
Middleware
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Advantages of ORBMiddleware
Anonymous interaction among applications Integrate new client/server applications with
existing legacy, mission-critical applications
Easier development environmentReduce cost
Improve time-to-market of applications
Enables distributed data environment
Enables dynamic web applications
db dbdbdb
Distributed Computing
Middleware
i f O
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Disadvantages of ORBMiddleware
Switching costs are high Upgrade from previous “Middleware” solutions
Requires high technical expertise Tend to outsource
Lengthy deployment time
db dbdbdb
Distributed Computing
Middleware
U l d I
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Unresolved Issueswith ORB
Security
ScalabilityRelated to network capacity
Rapidly changing technologies
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Distributed Computing
Middleware
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DBMS Applications
With advent of high-speed, distributed
architectures, expanded our use of database
beyond capturing and storing transaction dataKnowledge Discovery
Process of extracting useful knowledge from volumes
of dataSupported by:
Massive data collection (Data Warehouse/Data Marts)
Multiprocessor computing
On-line Analytical Processing (OLAP)/Data mining
db dbdbdb
Distributed Computing
Middleware
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Data Warehouse
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
db dbdbdb
Distributed Computing
Middleware
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MultidimensionalDatabase
OLTP not good when doing analysis of
data – poor performanceOLAP – on-line analytical processing
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Distributed Computing
Middleware
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“Slice and Dice” an OLAP Cube
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Advantages of OLAP
All hierarchical or aggregated values can be
pre-calculated in the cube rather than
accessing the WarehouseMajor reduction in query time
Each cube makes “business sense” Not normalized data structures
db dbdbdb
Distributed Computing
Middleware
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MultidimensionalDatabase (cont’d)
Data marts Scaled-down version of a data warehouse that
focuses on a specific areae.g., a department, a business process
db dbdbdb
Distributed Computing
Middleware
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Massive Data Analysis
Data mining Provides a means to extract patterns and
relationshipsExample: Analyze sales data to identify products that
may be attractive to a customerAmazon.com buyer suggestions
Two capabilitiesAutomated prediction of trends and behaviors
Automated discovery of previously unknown patterns
Example: Shopping cart analysis
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Distributed Computing
Middleware
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Network Enabling Software
Supplier Customer
Enterprise
Wide Systems
Enterprise
Wide Systems
Enterprise
Wide Systems
Supply Chain
Management
Customer
Relationship
Management
db dbdbdb
Distributed Computing
Middleware
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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
Internet Era
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Web-based Solutions
Early attempts to incorporate WWW intointer-organizational systems
Static, state-less web pagesComplicated navigation
Not “connected” to underlying data Page not dynamically updated when data changes
Web Services
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Hurdles for web services
Standards are evolving, not set
Security
Web services do not 'solve' interoperability
between applicationsHence – need ERP
db dbdb