Advanced Informatics Seminar

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Advanced InformaticsSeminar
University of Tartu, Winter 2000/2001
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Data Warehousing and Data Mining
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Where to find the information?

• no time basis of data
• ad-hoc calculation impossible
• the levels of detail
• the problem of external data
• no common source of data to begin with

?
Report
?
decision maker
operative systems (TPS)
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Data Warehouse- Definition

• A data warehouse is a subject oriented,
  integrated, nonvolatile, and time variant
  collection of data in support of managements
  decisions.

Inmon (1996), p. 33.
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Design the Data Warehouse

• the two major aspects of building of a data
  warehouse

interfaces to the operational systems
design of the data warehouse itself
? meta data
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MIS requirement definitioninformation objects
product group
Structure of reference objects
hardware
printers
computers
Reference object(year, product group,
customer, )
Informationobject
sales peryear 2000,product group
printers, customer all
Ratio number (sales)
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Technical MIS-architecture

• Data Warehouse
• Database for
• Management Information System

end user / analysis tools
OLAP
Data Mining Tools
Reporting
ABC, Portfolio-Analyis
modelling and administration
Data Warehouse
Management
Subject-oriented data marts
Data Warehouse
Tool
Meta data
extraction and transformation
external data
Operative Systems(TPS)
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MIS requirement definitionreport definition
?
Report
decision maker
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OLAPOnline Analytical Processing

• Relational model was not designed for data
  synthesis, analysis, and consolidation
• This is the role of spreadsheets and other
  special purpose software
• Need to complement RDBMS technology with a
  multidimensional view of data

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A hypercube
A B C ...
customer
Sales
juice coke milch ... ... ... ... ... apples grapes
banana
product
Dec. ... ... ... ... ... ... ... ... ... Febr. Jan
uary
Time
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Star Scheme
To minimize number of joins, data warehouse model
can be denormalized
Fact Table
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Drill Down
reference object
reference number
detailled information
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Possible Topics

• Potentials of Data Warehousing in Electronic
  Commerce
• Data Warehouse as Enabling Technology for
  Balanced Scorecards
• Data Mining in Business Applications State of
  the Art and Trends
• Principles of Multi-Dimensional Databases

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Internet and Electronic Commerce
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Internet and Electronic CommercePhases of
Transactions
Information and Decision Phase
Negotiation Phase
Performance Phase
Search for market partners and alternatives
Communicate about terms of conditions
Exchange good Payment
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Internet and Electronic Commerce(Exampe Market
Place)
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Possible Topics

• Theoretical Foundations of Electronic Commerce
• Personalization Approaches for Internet Portals
• Payment Models for Electronic Commerce
• Characterization of Electronic Market Places

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Knowledge Management
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Knowledge Management
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Content Management
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Possible Topics

• Methods and Tools for Knowledge Management
• Development of Content Management Systems

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Other Topics

• Methods of ERP System Selection
• Information Flows in ECR Co-operations
• Features of Customer Relationship Management
  Systems

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Methods of ERP System Selection(Example SAP R/3)
Enterprise Management
StrategicEnterpriseManagement
Business Intelligence Data Warehousing
Managerial Accounting
FinancialAccounting
Customer Relationship Management
Sales Channels
Sales Management
Service Agreements
Customer Service
Service Fulfillment
Product/Brand Marketing
Product Design Engineering
Computer Aided Design
Component Specification
Product Option Specification
Product Data Management
Manufacturing Process Specification
Engineering Change Management
Supply Chain Planning
Sales Demand Planning
Operations Planning
Distribution Planning
Component Procurement
Quality Evaluation
Component Supplier Selection
Purchasing Contracts
Electronic Procurement
Manufacturing
Production Scheduling
Production Execution
Quality Management
Plant Maintenance
Sales Distribution
Sales Cycle Management
Order Fulfillment
Distributor Reseller Management
Warehouse Management
Transportation Management
Customer Service
Installation Management
Field Service Support
Service History
Service Configuration Management
Billing/Costing/Profitability
Service Supply Chain Management
Business Support
Human Resource Management
Procurement
Treasury
Fixed Asset Management
Software Management
Foreign Trade Management
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Methods of ERP System Selection(Example
PSIPenta)
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ECR Pyramid
Interorganizational Information Flows in ECR
Cooperations
Efficient Product Innovation Efficient
Promotion Efficient Assortment Efficient
Administration Efficient Replenishment Efficient
Standards
Coope- rative Marketing
Logistics (SCM)
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Interorganizational InformationFlows in ECR
Cooperations
Wholesale trade/ Retailing Company
shared product development
Industry
Delivery order
Sales data
shared product develop- ment
Delivery order
Sales data
Supplier
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Features of Customer Relationship Management
Systems

• Definition Customer Relationship Management is
  the continuous creation and maintenance of
  customer relations, oriented at enterprise
  objectives (e.g. profit)
• Includes
• strategic functions (e.g. market segmentation)
• operational functions (e.g. order processing)
• Focusses customer orientation, but
• not maximizing customer orientation!
• as much customer orientation as necessary, as
  little as possible
• CRM tries to determine the optimal degree of
  customer orientation (-gt individualization)
• complexity costs of increasing individualization
  caused by increased number of process variants

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Features of Customer Relationship Management
Systems
Customer Life Cycle
2. Order Processing
3. After Sales
1. Acquisition

• 1. Acquisition
• First contact with customer
• Creation of first impression / company image
• least knowledge about customer (anonymous market)
• However Individual presentation required

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Features of Customer Relationship Management
Systems

• 2. Order Processing
• Reception and processing of customer order /
  request
• Already high degree of IT support (modules for
  material management, sales and distribution,
  production planning etc.)
• CRM requires
• integration of customer-related data from
  different sources
• possibilities to analyze links between customer
  and product data (identify customers causing
  increased product/process complexity)

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Features of Customer Relationship Management
Systems

• 3. After Sales
• Highest potential for CRM. Includes
• Inquiry of customer satisfaction
• complaint management
• customer support
• identify potential re-buyers and buyers of
  supplementary services or products
• drop likely non-re-buyers as soon as possible
• Independent offering of additional services,
  substitution parts etc. (generation of secondary
  revenues), enabled by analysis of
• average maintenance intervals,
• average product lifetime
• customer behavior,
• IT requirements Analysis of demographic data
  constant improvement of market segmentation