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This presentation contains live Architecture patterns for B2B and B2C setup with Master Data Management (MDM) Concepts.
Using this presentation one can simulate to their Big Data planning process from different business interfaces.
They can use these frameworks and definitions for their internal business applications architecture current and future setup, once the Big Data handling framework is designed for an IT Organization.
This can be extended depends on their future Big Data handling solution engineering.
Master Data Management (MDM) and Enterprise Architecture (EA) Setup & Solutions
1. Master Data Management (MDM) and
Enterprise Architecture (EA) setup
1
This presentation contains live Architecture patterns for B2B and B2C setup with MDM Concepts.
Using this presentation one can simulate to their Big data planning process from different business
interfaces.
They can use these frameworks and definitions for their internal business applications architecture
current and future setup, once the Big data handling framework is designed for an IT Organization.
This can be extended depends on their future Big data handling solution engineering.
2. MASTER DATA MANAGEMENT
Change Management lacks process control (Spreadsheets, Phone & Email)
Bulk: ETL, Custom
Transactional: EAI
Real time: EII
Data
Legacy
G/L Operational
Hierarchy
Processes
Hierarchy
Processes
Hierarchy
Processes
Metadata
Processes
G/L Maps
ProcessesHierarchy
Processes
vMapping
Processes
Excel
Excel
App Files
Access
DB
VSAM
File
Excel
Profitability
Corporate
Reports
Data
Warehouse
AccountingScorecard
Marketing BPM
Fact
Data
Fact
Data
Fact
Data
Fact
Data
Metadata
Processes
Excel
Data
Oracle
Financial
Any
System
SAP
Hierarchies
Dimensions
Reference Data
Business process management
G/L-general/ledger
virtual system access method
Special Assistance Plan
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3. Types of Data Management Systems
Three different types of data management systems at a
very high level :
•Transactional data management system
•Analytical data management system
•Master data management system
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4. Master data
• Master data is the enterprise-wide data and facts
describing key business entities.
Facts and relationships among customers, employees
Partners
Suppliers
Details
Facts
Hierarchies of products
Items
Materials
Bill of materials.
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5. Master Data Management (MDM)
Architecture
Patterns:
MDM architecture
pattern
MDM solution pattern
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6. Collaborative method
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7. Operational method
The operational style of MDM supports the
Consumption of master data by operational systems to
perform transactions and
The MDM repository is considered the authoritative source
of master data.
Furthermore, in operational mode, master data is leveraged
by:
Applications through services
Control over master data creation
Management
Quality and
Access
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8. Analytical method
Uses of analytical method:
Reducing the risk of increased costs and
Mitigating potential damage to an organization's
reputation.
For example, identity analytics can be used to
Detect threat
Fraud scenarios
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9. Master Data Management
Architecture Patterns
Multiple Master Data Management architecture
patterns:
• MDM application integration patterns
• MDM information integration patterns
• MDM enterprise system deployment patterns
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10. MDM enterprise system deployment
patterns
•MDM enterprise system deployment patterns:
– MDM business intelligence (BI) analytical pattern
– MDM data warehouse pattern
– MDM multiple system pattern
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11. Registry Style
Registry implementation style provides
Quick to deploy
Lower cost compared to the other styles
Providing read-only views to all master data
records in the IT landscape.
Remove duplicates
Consistent access path to master data
Enforce uniqueness
Cross-reference information
31
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12. Product Mapping
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13. Conclusion
• The creating and maintaining of accurate and
complete master data is a business imperative.
• Both large and small businesses must develop
data-maintenance and governance processes and
procedures, to obtain and maintain accurate
master data.
• It's easy to think of master-data management as
a technological issue, a purely technological
solution without corresponding changes to
business processes and controls will likely fail to
produce satisfactory results.
37
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14. 1
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