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Fact Oriented Modeling
- Marco Wobben -
Why ‘fact oriented’ ?
FCO-IM
https://time.graphics/line/114267
What to build?
How to get there?
Are you sure?
Involve the experts
What if … ?
• Using natural business language
• Agile every step of the way
• Validated by domain experts
• Integrated documentation
• Multiple language domains supported
• Model once, bootstrap everything
Just do IT…
Different Mindset
NOT:
tables, entities, classes,
columns, or properties…
BUT:
Find, verbalize, model and
validate facts…
Relations = Building Blocks
Fact Oriented Modeling
Transformations
Get started…
Modeling by Example
Collect
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Verbalize
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Modeling by Example
Model
Validation
Rule Validation
Rule Validation
Wizard Validation
Expert Validation
Well-Formedness
Model Transformations
how does that work?
Example
“Customer 4081 is Sandia Labs.”
Customer
Customer NoName
Name of Customer
Example
Customer Location City
City Name
Customer
Customer NoName
“Customer 4081 is Sandia Labs.”
“Customer 4081 is located in Albuquerque.”
Name of Customer
Group (before)
“Customer 4081 is Sandia Labs.”
“Customer 4081 is located in Albuquerque.”
Customer Location City
City Name
Customer
Customer NoName
Name of Customer
Group (after)
City
City Name
Customer
Customer NoName
“Customer 4081 is Sandia Labs.”
“Customer 4081 is located in Albuquerque.”
Lexicalise
City
City Name
Customer
Customer NoName
“Customer 4081 is Sandia Labs.”
“Customer 4081 is located in Albuquerque.”
City
City Name
Customer
Customer NoName
Reduce
“Customer 4081 is Sandia Labs.”
“Customer 4081 is located in Albuquerque.”
SQL DDL
CREATE TABLE Customer (
Customer_No integer NOT NULL,
Name varchar(64),
City_Name varchar(256),
PRIMARY KEY (Customer_No)
);
City Name
Customer
Customer NoName
Model Transformations
transform into what?
Concept Map
OWL/RDF Semantic Web
XML Schema
JSON Schema
UML Class Diagram
Logical Diagram
SQL (DDL+DML)
transformations into ..
DBMS
Oracle
SQL Server
MySQL
SQLite
SQL92
MongoDB
Interbase
MsAccess
Denodo Data Virt.
…
Miscellaneous
PowerDesigner
OWL/RDF
XML Schema
App Generators
DWH Models
Relational Diagrams
UML Class Diagrams
HTML + Images
Spreadsheets
…
Data Vault
Transform an
information model
into a
data vault model
when generating
implementation artifacts.
Links
Hubs
References
Satellites
DV Receipt
• Reduce unused Object Types
• Name hidden Object Types
• Static Fact Types : Reference Tables
• Fact Types (business keys) : HUB
• Groupable Fact Types (+transaction) : SAT
• Roles played by Object Types : LINK
Fact Oriented Model
DV Coloring
DV & Business
• Generate (SQL) data model for
data storing in Data Vault
• Generate (SQL) views based upon
conceptual information model
to represent the Business Vault.
• Generate (SQL) unified views based upon
business communication
to verbalize the Business Vault.
Summary
CaseTalk Viewer
• Simplified FCO-IM
• Logical Diagram
• UML Class Diagram
• Concept Map
CaseTalk Manager
• Multi Models
• Versions & Tags
• Users & Permissions
• Microsoft SQL Server
Lost in Translation
Communication
Excellent for…
High Quality
High Complexity
High Volumes
Strict Governance
Advantages
• Expert participation
• Conceptual approach
• Extremely agile
• Rooted in real business examples
• Business language as input ánd output
Advantages
• Expert participation
• Conceptual approach
• Extremely agile
• Rooted in real business examples
• Business language as input ánd output
Contact
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Fact oriented modeling