Helfert Research Approach for Measuring IQ
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Transcript of Helfert Research Approach for Measuring IQ
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8/3/2019 Helfert Research Approach for Measuring IQ
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HSG / IWI / CC DWS
Markus HelfertInstitute of Information Management
University of St.Gallen
datawarehouse.iwi.unisg.ch
Data Warehousing Strategie
Renate RadonEpicur GmbH
Germany
www.epicur.net
Research Approach
for Measuring Information Qualityin Data Warehousing
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Data Warehousing Strategie
EPICUR Competencies
Finance & Administration
Payroll
Project Mgt.
Engineering
Service Mgt.
Discrete Man.
Core Competencies
Shared
Servic
es
Supplier Integrator Customer
E-Services
Business Bus
Intranet
Extranet
InternetCustomerRelationshipManagement
Adding Economic Value Business Intelligence Business Networking
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Data Warehousing Strategie
Competence CenterData Warehousing Strategy
Business Case / Cost Benefit Analysis DWH Introduction
Organizational Concepts
Information Requirement Analysis Data and Information Quality
Operational Data Warehouse
Research Project covering areas of
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Data Warehousing Strategie
Content
Data Warehouse - turntable for business process integration
Information Quality and Information Characteristics
Quality Function Deployment
An Example: Process of Product Configuration
Further Research
Method-based Information Quality Management
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Data Warehousing Strategie
Turntable for End-To-End
Business Process Integration
StructureP
rocesses
TransactionalProcesses
Information
Processes
E-BusinessProcesses
Data Warehouse
Marketing
InternetMarketing
Marketing
Analysis
Sales Internet Sales
Configuration
Business Part-
ner Collaboration
. . .
Service
Service
Interaction
Field Service
Customer RelationshipManagement
nProvide value-addinginformation at any time,any location, any level
of detail, any individual
request
n Decompose traditional
value chains and recompose
according to informationchains
nAdd value to your busi-
ness partners by providingreliable, high-quality
information Operational Processes
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Data Warehousing Strategie
Traditional Products + Information = Solution
Pricing
Conditions
Formse.g. Proposals,
Invoices, Payments,etc.
Media
Business
Partners
Competitors
Others
Electronic
Catalogue
Configuration, Billing, Payment
Special Offers
Purchasing
Announcements
Product
Developmen
t
Product
Information
Manufacturin
g
Methods
Technical
Know-How
Sales
Inventory
Management
Assortment
Distribution
Contact
Management
Proposal
Managementt
Service
Management
Influencers
Data Warehouse
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Data Warehousing Strategie
Information Quality
Characteristics of information whichmeet user requirements and therebyprovide user satisfaction
Absence from informationdeficiencies that result in userdissatisfaction
Framework to specify information requirementsand measure information supply
on a uniform and consistent base (set of relevant information characteristics)
Information Process powned by user u
Information supplyfor process p and user u
Information requirementsfor process p and user u
=Correspond?
Informationsources
One accepted approach is focused on user and product fitness for use (Juran 1998)
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Data Warehousing Strategie
Information System
Information, Data and Signals
Signals
(Characters, symbols)
Data
Information
Syntax
Semantic
Pragmatic
Real World
Example
09/03/00
09/03/00 DD/MM/YY
String containing numbersNN/NN/NN
Expected Date, when the productcan be delivered to the customer
Application
Interpretation
Representation
Expected Delivery Date
Product configuration
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Data Warehousing Strategie
Information Quality Characteristics
Syntax
Semantic
Pragmatic
Syntactical correctness, consistentrepresentation,
security, accessibility
Interpretability, accuracy, consistent data
values, complete data values, precise data
definitions, objective, believability, reliable, easyto understand
Relevance, completeness, timeliness
Semiotic Level Information Quality Characteristics
Research Questions Precise Definition of information characteristics Correlation between user requirement and information characteristics
Methods and techniques for measuring information characteristics
Measurement
InformationProcess(Usage)
Real World
(Comp. with
experience andhistorical data)
SyntacticalStandards and
Agreements
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Data Warehousing Strategie
Method-based IQM
Method-based IQM
Organizational
structure
(roles and
responsibilities)
Process
organization
Methods
Techniques and
Tools
Standards, Rules
and Guidelines
Definition of informationcharacteristics and assess
quality goals
Identify and Implementsteps to improve continuously
information quality
Quality Estimation and
Measurement
User Requirements
Causes
Quality deficiencies
Consequences
Analyze
Analyze
Information Process
Information Supply
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Data Warehousing Strategie
Quality Function Deployment
Information characteristics
Userrequirements
Measurementbased on userrequirements
Measurement based onInformation characteristics
Target value
Correlation of
characteristics
Priority
Correlation
Introduced by Akao in Japan in 1966 (Manufacturing Sector)
Customer requirements as focus Method for quality planing
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Data Warehousing Strategie
Configuration as an example for
Information Quality Measurement
Load Know-ledge Base
Assigncharacteristicvalues
Checkcomplete-ness
Multi-levelinteractiveconfiguration
SaveConfi-guration
PriceConfi-guration
Classification
Materials
Dependencies
Customer-designedProductDefinition
Customer-designed&
consistency-provenProduct
GraphicalProduct Structure
Customer-
designedProductCustomer-individually
configured &priced Product
Know-ledgeBase
Prices &
Conditions
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Data Warehousing Strategie
Load Know-ledge Base
KnowledgeBase
Availibility ofProductInformation
Delivery
Date
CountryspecificFeatures
ProductDescrip-tion
ProductVersion
Configuration as an example for
Information Quality Measurement
Completeness
Relevancy
Relevancy
Completeness
Timeliness
Semantic
Pragmatic Information
Characteristics
Syntactic
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Data Warehousing Strategie
Corre
lation
Correla
tion
Measurement
Measurement
Example Product Configuration
Delivery Date (always)
Product description (if possible)
Availability of product information
Relevancy Completeness Timeliness
X
XX
X
Precise Definition for Delivery Date
Correct Delivery Date (no default value)
One Delivery Date for a product
Interpretability Accuracy Complete
data Values
Consistent
data Values
X X X
X X
X
X
unusedinformation
additional informationrequests
not timely availableinformation
Non interpretabledata values
Incorrect datavalues
Empty valuesInconsistentdata values
% of
% of
Pragmatic
Semantic
...
...
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Data Warehousing Strategie
Further Research
Generic House of Quality for each semiotic level
Integration of level specific Houses of Quality in a Model of Information Quality
Relations between requirements, characteristics and semiotic levels
Methods and techniques for measuring information characteristics
Methods to apply the Model for specific information processes (e. g. Product
Config.) Validation of research results in practical projects (e. g. Customer Relationship
Management)
Model of Information Quality as basic framework