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Enterprise Resource
Planning
Module II
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ERP Module II Prepared By: Ms. Swapna Anildas 2
Topics Covered
Technical Architecture of ERP systems
Distributed computing
Client server systems
Concept of business objects
Distributed object computing architecture
Support for data mining and warehousing
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Technical Architectures of ERP
Two-tier Architecture
Three-Tier Architecture
Web-based Architecture
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Two-Tier Architecture
The server handles both application and
database duties The clients present the data and pass user
input back to the server.
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Two-tier Architecture
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Server:
Application and
Database
Clients: Input and
Presentation
Presentation Layer
(GUI Applications)
Data
Applications/
Database Layer
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3-Tier Architecture
Database and application functions are
separated.
The three layers: Presentation Layer
Business Logic / Application Layer
Data Management Layer
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Three-tier Architecture
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Database Server
Local / Remote
Clients
Application Server
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Presentation Layer
The top most layer of application in which
the user interacts with the system.
Screen layout, Navigation, language
integration, and other user based elements
are controlled in this layer.
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Business Logic Layer
This layer coordinates the application,
processes commands, makes logical
decisions and evaluations, and performs
calculations
It also moves and processes data between
two surrounding layers.
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Data Management Layer
Here information is stored and retrieved
from a database or file system. The
information is then passed back to the logic
layer for processing and then eventually
back to the user.
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Presentation Layer
Business Logic Layer
Data Management Layer
Get Sales
Total
Total
Sales
Get list of all sales
made last year
Add all sales
together
DB
QuerySales 1
Sales 2
Sales 3
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Web-based Architecture
The main reason for the migration of ERP systems into the
Web is to improve their competitiveness, companies need to
drive collaborative business. Implementing this collaborativebusiness requires integrating their existing heterogeneous IT
landscapes and extending this integration to their business
partners, customers and suppliers. Internet appears as the
solution for integrating different applications belonging to
different Information Systems. To answer to these newrequirements, vendors have developed a new generation of
ERP systems based on the Web technology: the Web-based
ERP.
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Web-based Architecture..contd.
The fundamental advantage of Internet is that it is a
standards-based environment with no owner, so nobody can
claim to have new and improved Internet. Any companycan access to a web-based ERP as long as it has an Internet
connection and the right authorization. The Web allows the
creation of an open platform that will permit different
applications to communicate easily through the standardsoffered by Internet.
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Web-based Architecture..contd.
In essence, a web service is three specific things :
A way to find and register interest in a service (UDDI)
A transport mechanism to access a service (SOAP)
A way to define what the input and output parameters are for
such a service (WSDL)
Web services represent an independent platform, not
controlled by any one vendor that provides a way to allow
applications to talk to one another. To communicate using
web services, applications first have to find the service that
is located in a library called UDDI (Universal Discovery,
Description, and Integration).
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Web-based Architecture..contd.
The UDDI sends the service to the client with the
defined interface, then the application can
communicate with the service through a
standardized protocol called SOAP (Simple Object
Access Protocol) built-up using an XML schema.
The following schema (see Figure 7) shows these
different actions:
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Web Based ERP Architecture
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Centralized vs. Distributed Computing
mainframe computerworkstation
network host
network link
terminal
centralized computing
distributed computing
Early computing was
performed on a single
processor.Uni-processor
computing can be
called Centralizedcomputing.
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Centralized vs. Distributed Computing
mainframe computerworkstation
network host
network link
terminal
centralized computing
distributed computing
A distributed system is a collection of
independent computers, interconnected
via a network, capable of collaborating
on a task.
Distributed computing is computing
performed in a distributed system.
Distributed computing has become
increasingly common due advances thathave made both machines and networks
cheaper and faster
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Example Distributed systems
Internet
ATM (bank) machines
Intranets/Workgroups
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Computers in a Distributed System
Workstations: computers used by end-users to
perform computing
Server machines: computers which provide
resources and services
Personal Assistance Devices: handheld
computers connected to the system via awireless communication link.
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Goals/Benefits
Resource sharing
Scalability
Fault tolerance and availability
Performance
Parallel computing can be considered a subsetof distributed computing
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Components of Distributed Software Systems
Distributed systems
Middleware
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Challenges(Differences from Local Computing)
Heterogeneity
Latency
Remote Memory vs. Local Memory
SynchronizationConcurrent interactions the norm
Partial failureApplications need to adapt gracefully in the face of partial
failure
Lamport once defined a distributed system as One onwhich I cannot get any work done because some machine Ihave never heard of has crashed
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Challenges.contd
Need for openness
Open standards: key interfaces in software andcommunication protocols need to be standardized
Security
Denial of service attacks
Mobile code
Scalability Transparency
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Distributed applications Applications that consist of a set of processes that
are distributed across a network of machines and
work together as an ensemble to solve a commonproblem
In the past, mostly client-server
Resource management centralized at the server
Peer to Peer computing represents a movement
towards more truly distributed applications
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Data MiningandData MiningandData WarehousingData Warehousing
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Introduction
Organizations getting larger and amassing ever
increasing amounts of data
Historic data encodes useful information aboutworking of an organization.
However, data scattered across multiple sources,
in multiple formats.
Data warehousing: process of consolidating datain a centralized location
Data mining: process of analyzing data to find
useful patterns and relationships
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What is Data Mining and Knowledge
Discovery ?
Data Mining is a tactical process that uses
mathematical algorithms to sift through large data-
stores to extract data patterns/models/rules The Knowledge Discovery is the process of
identifying and understanding potentially useful
hidden anomalies, trends and patterns. Data
mining is an integral part of knowledge discoveryprocess
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Typical data analysis tasks
Report the per-capita deposits broken down by
region and profession.
Are deposits from rural coastal areas increasingover last five years?
What percent of small business loans were cleared?
Why is it less than last years? How did similarbusinesses that did not take loans perform?
What should be the new rules for loan eligibility?
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Bombay branch Delhi branch Calcutta branch
Census
data
Operational data
Detailed
transactionaldata
Data warehouse
Merge
Clean
Summarize
Direct
Query
Reporting
tools
Mining
tools
Decision support tools
Oracle SASIMS
Crystal reportsIntelligent Miner
GIS
data
OLAP
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Data warehouse construction
Heterogeneous data integration merge from various sources, fuzzy matches
remove inconsistencies Data cleaning:
missing data, outliers, clean fields e.g. names/addresses
Data mining techniques
Data loading: summarize, create indices Products: Prism warehouse manager, Platinum info
refiner, info pump, QDB, Vality
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Warehouse maintenance
Data refresh
when to refresh, what form to send updates?
Materialized view maintenance with batch
updates.
Query evaluation using materialized views
Monitoring and reporting tools
HP intelligent warehouse advisor
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Mining market players
Major players:
Clementine, IBMs Intelligent Miner,
SGIs MineSet,
SASs Enterprise Miner.
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Business Data Mining Applications
Area Applications
Retailing Market basket analysis, cross-sell
Banking Customer relationship mgmt
Credit Card Mgmt Lift, churn
Insurance Fraud detection
Telecommunications Churn (customer turnover)
Telemarketing On-line caller information
Human Resource Mgmt Churn (employee turnover)
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End of Module II