session 9 information architecture for e-business · session 9 information architecture for...

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Gestão de Informação Aula 2 - Arquitectura de Informação para o e-business Prof. Paulo Cardoso do Amaral 1 -

Session 9Information architecture for e-business

l Enterprise Resource Planningl Supply Chain Managementl Costumer Relationship Managementl Selling Chain Managementl Enterprise Application Integrationl Systems architecture for e-businessl Datawarehousingl Decision support systems and dataminingl Executive information systemsl Operational data storel Data quality


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Sales & Production Finance Accounting HRM

Strategic level Officers

Coordination Managers

and control

Operations Workers

Marketing





and control

Operations Workers

Marketing

TPS

TPS - Transaction Processing Systems•Operational level• Business transactions and routines

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and control

Operations Workers

Marketing

OAS

OAS - Office Automation ou Escritório ElectrónicoWord processis, agenda, e-mail, kbs

TPS





and control

Operations Workers

Marketing

OASTPS

MIS - Management Informations SystemsReports, planned and ad-hoc

MIS

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and control

Operations Workers

Marketing

OASTPS

MIS

DSS - Decision Support SystemsData, nformation and dececion models

DSS





and control

Operations Workers

Marketing

OASTPS

MIS DSS

ESS - Executive Support SystemsTableaux de bord

ESSESS

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Enterprise Resource Planning

l Origin:– EQO (50s), MRP (60s) MPS BM CRP, MRPII (80s)

l ERP - software integrated solution– automate functional areas– automate integrated business processes

» Data sharing across the enterprise

– Data use in real-time– modules

» finance, accounting, payables and receivables» Human resource management, production» Maintenance, logistics, distribution, quality


Operational systems development

l 1. Analysis and programming» Programming languages, data bases» Software engineering

l 2. parameterization of packages» At least 80% of needs

l Adopt rather than adapt

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Procurement of operational systems

l Strategic objectivesl Request for Information - RFIl Set of Requirementsl “Caderno de encargos”l Request for Proposals - RFPl Gap analysisl Project


SCMSupply chain is the set of structures and activities that ensure seamlessly the flow of materials, products, services and information between the business, its suppliers and final consumers

Supply chain management targets the efficiency increase of the supply chain by the coordination of suppliers, producers, distributors and retailers and management of operational activities

Produ Distribuidorsupplier retailers Client

Materials Products Products Products

Information

Producers DistributorsSuppliers retail Client

MaterialsMaterials ProductsProducts ProductsProducts ProductsProducts

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Supply Chain Managementl So it links suppliers, producers, transporters and

distributors to– Ensure the flow of products and materials– optimize the supply chain in real-time– Considers, at the sae time, the product demand, and capabilities

and constraints of the participants in the value system

l Demand Planning (historical)

l Supply Planning (to avoid stockouts)

l Manufacturing scheduling (the best schedule fit)

l Transportation Planning (the best warehouse and transport fit)


Customer Relationship Management

l Integrated management of clients’ contacts» Call-centre vs. Contact Centre» telephone » Internet» Multimedia, WebTV, 3G, ...» (Knowledge Management Systems)

l Information and knowledge about the client– Who is the client– And his behaviour

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CRM benefits

l Better quality of service– Use of a contact centre

l Lower cost– Use the right channel to the right transaction for each

costumer

l Anticipate need– Increase loyalty, decrease churn

Resultado

Clientes


Costumer Relationship Management

l Interaction platform– Sales Force Automation– telemarketing, telesales

» cross-selling, up-selling– pro-active service and self-service

» Loyalty programs

l Information platform– Campaign management– Consumer behaviour analysis– Contact register– profiling

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Selling Chain Management

l Order life-cycle managementl Steps:

– Prospect identification– Product catalogue– Product configurator– Proposal generation– Quotation manager– Order management– Commissioning– Contract management


Enterprise Application Integration

l Modern enterprises need more than simple BPR:– > sharing information between processes– > innovate complex processes faster– > overall data management to create knowledge

l EAI is more than middleware– Data transport– Data representation– Business rules definition and processing

» Smart routing» Event processing

– Business process definition and execution

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ERP - SupportAccountingHRMProcurement

Planning:- Order- demand- Transport- Distribution- scheduling

ERP

LogisticsProductionDistribution

Finance

CRM

Service Direct Mrk

Up, Cross SellSFA

Systems architecture for e-business

Datawarehouse+

DataminingSupplyChainMngt

SellingChainMngt

EAI

ProposalsBudgetCatalogCostumizerPricingContractCommissioningOrder

EnterpriseApplicationIntegration


TPSOAS MIS

KWS

DSS

ESS

ORGANIZATIONAL LEVELTYPE OFDECISION OPERATIONAL KNOWLEDGE MANAGEMENT STRATEGIC

STRUCTURED ACCOUNTS RECEIVABLE

ELECTRONIC PRODUCTIONSCHEDULING COST OVERRUNS

SEMI- BUDGETSTRUCTURED PREPARATION

PROJECTSCHEDULING

FACILITYLOCATION

UNSTRUCTURED PRODUCT DESIGN NEW PRODUCTSNEW MARKETS

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Information Systems!

l First step in transforming data in informationl Management effectiveness with reports

» Management have access to information when they need it l Planned and ad-hoc

l 80s: the Personal Computer revolution– Data and information in the hand of the end-user

» But costs have also increased» And new coordination mechanisms are necessary

l 90s: Datawarehousing and Decision Support Systemsl 2000: information and knowledge in real-time

– Operational Data Store


MIS

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l A Decision Support System is:– Na Information System with data, decision models and an

ergonomic user interface to support semi-structured decisions

l Characteristics– Supports managers at all levels– Adapts both to users and needs– Should be effective– Is interactive under the control of the end-user

Decision Support Systems (DSS)


OLAP

•

•

•

•

•

•

Integrated (clean)

Management oriented

HistoricalActual

Applicationoriented

Normalized

. . . Data models are different!

OLTP (ex: ERP)

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Example of a logicaloperational data model


Example of a physicaloperational data model

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Gestão de Informação Aula 2 - Arquitectura de Informação para o e-business Prof. Paulo Cardoso do Amaral 27 -3 .

“Star Schema”model


What are data hierarchies used for?

l Data hierarchies describe data the organizational structure and father-son relationships

l Allows data to be “drilled-down” more detailed levels

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Multidimensional Aggregations


DSS

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Data to information life-cycle

Metadata

InternalData

ExternaDatal

Operational data Data Warehouse

ExtractionTransformationLoad Analysis

QUERIES &REPORTS

OLAP

DATA MINING


Data to information life-cycle

Extraction

TransformationCleansing

Load

Exploitation

Mining,Analysis

Manageand

Automate

Feed-backERP’s

Procurement

Accounting

Billing

Legacy Systems

Data Warehouse

DataMarts

DataMarts

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DataWarehousing architecture

Preparationand tranport

Warehousing

Presentationinterpretationand Analysis

Extraction, Transformation, Load Cleansing

Metadata

Relacional DB (not normalized)

Multidimensional DB

OLAP/EIS Internet Repporting Ad-hoc

QueryBusiness

ApplicationsDevelop.

LanguagesData

Mining

OperationalSystems


Ex. of DataWarehousing tools

Preparationand transport

Warehousing

Presentationinterpretationand Analysis

Prism, ETI, Informatica, InfoSage, SAS, Microsoft SQL Sever - DTS Vality, DataStage, Trillium

Microsoft SQL Server, IBM Visual Warehouse, SAS WA

Oracle, DB2, SAS Data Sets, MS SQL Server, Informix

SAS MDDB, Gentia, Microsoft OLAP Services , Essbase, DB2OLAP, Oracle Express, Holos

BoardSAS/EISGentia

BOCognos

Oracle Express

SAS/I-netExplorerNetscape

GentiaBrio Portal

BO web

SAS ERCristal

Oracle Rep.Forest Trees

Business ObjectsBrio

ImpromptuBusiness Objects

MicroStrategyInfo Advantage

SAS ERBusiness Objects

Gentia BSCSAS CFO Vision

ProfilimpactOracle Sales

AnalyserSAP BW

Visual BasicJavaSAS

Intelligent MinerEntreprise Miner

Clementine

OperationalSystems

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Knowledge Discovery in Databases

– Selection» Following some management objective

– Pre-processing» cleansing, fill-in the gaps

– Transformation» According to business rules

– Datamining– Interpretation


Examples of main Data Quality problems

l Flawed operational data models– Inconsistent data server only simple transactions

» Names, addressee, multiple keys and bad normalization, ...

l Inconsistent operational data models– Have to be consolidated

l Data in the wrong field– Ex: text field use

l The nightmare for consolidationl Data in programs

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Data Quality

1. Parsing, a question of semanticsl Depends on the correct use of the operational data model

2. Correction3. Standardizationl Titles, genre

4. Enrichmentl When essential data is missing

5. Matchingl Eliminate duplicates

6. Consolidationl When information is really created\

7. Charging


Datamining

l Classification – from relational to multi-dimensionalityl Association – high probability patternsl Sequential analysis – time patterns

l Cluster analysis

l Algorithmics– Probability Value Prediction– Regression forecasting– Time Series Forecasting– Decision trees – cause-effect relationships– Artificial Intelligence

» Rule induction» Rule deduction» Neural networks

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Operational Data Store

l The need for information and knowledge in real-time is increasing

l The Datawarehouse is the persistent repository of explicit data, information and knowledge but it can hardly be used in real-time

l The Operational Data Store is and architectural important tool that provides operational use of Datawarehouse data

session 9 information architecture for e-business · session 9 information architecture for...

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