IBM Industry Data Models
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1 IBM Software Group IBM Industry Data Models Usage, Process & Demonstration David Cope EDW Architect Asia Pacific 2007 IBM Corporation
2 The EDW Data Model Business Requirements Analysis Design Planning Data Modeling Construction Test and Load Data Analysis Training One of the essential components in the deployment and consolidation of data warehouses and data marts is the data model the logical design specification of the databases. Such Information Models are the accepted way of designing all databases. Data models are critical path inputs to load process (ETL) design. And a data model failure almost certainly results in lots of re-work: RE-WRITE ETL scripts and RE-RUN extractions RE-CREATE databases and RE-LOAD data RE-OPTIMIZE physical data base(s) RE-DESIGN and RE-BUILD OLAP applications RE-TESTall ETL and OLAP pplications RE-TRAIN end users 2
3 IFW Components and Relationships OSS/BSS Data Sources mapping XSDM Services Data Model (XSDM) Classification model for defining business meaning across all models and databases OSS/BSS Data Sources Logical E-R Models for ODS source systems XML Bridge Metadata Bridge ETTL XDW M BSTs Industry Data Model (XDWM) Logical ER Model for designing central data warehouse mapping Business Solution Templates (BSTs) Logical Measures and Dimensions for defining and presenting key performance indicators (KPI's) IBM s IBM s solution solution is is unique unique there there are are a a handful handful of of Data Data Warehouse Warehouse models models available, available, but but IBM s IBM s solution solution is is accompanied accompanied by by Model Model Management Management Tooling Tooling (m1) (m1) to to utilize utilize the the power power of of the the structure structure and and deploy deploy a a full full data data classification classification across across core core business business functions, functions, further further accelerated accelerated by by fast-start fast-start Solution Solution Templates. Templates. 3
4 Cla ssific atio n Cla ssific atio n Entity Na me Entity N ame Field-1-1 (PK) (PK) Field-2 Fie ld -2 Field-3 Fie ld -3 Ve Very Lon Long g Fie Field ld-4-4 Ve ry Lon g Fie ld-5 Very Long Field -5 Entity Na me Entity Name Field- 1 (PK ) Fie ld -1 (PK) Field- ld 2-2 (FK (FK) ) Field- 3 Fie ld -3 Field- ld 4-4 Field- 5 Fie ld -5 Field- ld 6-6 Field- 8 Fie ld -8 Field- 9 Fie ld -9 Field- ld Entity Entity Na N ame Fie ld-1 (PK) Field -1 (PK) Fie Field ld-2-2 (FK) (FK) Fie ld-3 Field -3 Fie Field ld-4-4 Fie ld-5 Field -5 Fie Field ld-6-6 Entity Na me Field- 1 (PK ) Field- 2 (PK ) Entity Entity N Na ame me Field -1 (PK) Field-1 (PK) Field Field-2 (FK) (FK) Field Field-3 (FK) (FK) Fie ld -4 Field- 4 Fie Field Fie ld -6 Field- 6 Entity Na me Field- 1 (PK ) Field- 2 (PK ) Entity N am e Entity Na me Field- ld 1-1 (PK (PK) ) Field- 2 (FK ) Fie ld -2 (FK) Field- ld 3-3 (FK (FK) ) Fie ld -4 Field-4 Fie Field-5 Fie Field-6 Entity N am e Fie ld -1 (PK) Fie ld -2 (FK) Fie ld -3 (FK) Entity Na me Entity N am e Field-1-1 (PK) (PK) Field-2 (FK) Fie ld -2 (FK) Field-3-3 Field-4 Fie ld -4 Field-5-5 Field-6-6 Ve ry Lon g Field-7 Very Long Field -7 Ve Very Lon Long g Field-8-8 Cla ssific ation Entity Entity Na N am me e Field-1 (PK) Fie ld -1 (PK) Field-2-2 (FK) (FK) Field-3-3 Field-4 Fie ld -4 Field-5-5 Field-6 Fie ld -6 Entity E ntity N Na am me e Fie ld -1 (PK) Field-1 (PK ) Fie ld -2 Field-2 Fie Field-3 Cla ssific ation IBM Software Group IFW Components in Physical Architecture Business Definition Synchronization Scoped XSDM Map Customized BSTs Legacy OSS/BSS Billing OE/OM Campaign OE/OM Mgmt CRMS OE/OM OE/OM POS OE/OM HR Collections OE/OM Commissions OE/OM A/P, OE/OM A/R, G/L OE/OM Scoped XDWM ETL EDW ERD Engineering Data Warehouse Mining Vectors Aggregations Scores & Propensities MOLAP Data Mining Star Schema Engineering ROLAP 4
5 The Services Data Model (TSDM) The XSDM is an object class hierarchy based on classification theory. There are 5 levels in the TSDM: A, B, C, C and D A B C C D Business Subjects Data Classifications Reusable Entities Application Entities Table Structures There are 9 subject areas in the TSDM: Involved Party, Arrangement, Event, Product, Location, Resource Item, Condition, Classification and Business Direction. The XSDM organizes these 9 data concepts first by Instance or Type and then as Fundamental, Associative and Attributive. 5
6 The Nine Data Concepts in XSDM The 9 Data Concepts in the Services Data Model provide a generic overview of the data in an enterprise 6
7 Industry Data Warehouse Model (XDWM) Arrangement Event INSTANCE TYPE Involved Party ASSOCIATIVE Location Classification Product Condition Resource Item FUNDAMENTAL ATTRIBUTIVE Business Direction 7
8 XDWM Content and Structure Concept The set of Concept Fundamental (subtype) hierarchies will form the "skeleton" of an implemented ER model All other data attaches to this skeleton Known as Fundamental Entities 8
9 XDWM Content and Structure Concept Descriptor The set of Concept Descriptor (property) hierarchies will form the attributes of an implemented ER model Also supplementary entities known as Attributive Entities e.g. repeated data 9
10 XDWM Content and Structure Concept Relationship The set of Concept Relationship hierarchies will form the relationships of an implemented ER model Also many-to-many entities known as Associative Entities 10
11 XDW Implementation Approach BST s Workshops Use JAD Sessions to customize multiple BST s Express Requirements in Enterprise Context Defines Critical Information Elements and assists in the identification of candidate data sources and change data capture specification Cross- Reference to Requirements Information Framework Develop the framework for a crossfunctional Enterprise Information Architecture and specifies common (and divergent) definitions of business definitions Implement the PDM to support users analysis requirements Customize the XDWM to capture specific requirements Expand Framework into a Subject Area Specific Model Physical Data Model Refine design decisions and expand the Physical Data Model Logical Data Model Cross- Reference to Requirements and map to XDWM Conceptual Data Model 11
12 Why use the IFW Solution Provides a Jump Start for analysis of warehousing requirements Includes Pre-Defined OLAP structures for analysis Pick and Choose Measures and Dimensions from Best Practise Has Consistent Structures and Common Definitions Is fully Customizable - scope required elements and add if required Completely Re-usable logical data model structures 100% Synchronized across XSDM, XDWM, BST & AST Supports Rapid Development 12
13 IFW Demonstration Conducted using the Banking Data Warehouse Model 13
14 IFW Comparison with other models BENCHMARK Information Framework Data Consolidation and Scalability Industry Coverage Extensibility Software Support Open Solution IBM IFW The IBM xsdm classifies and documents every entity, attribute, relationship and domain in the xdwm. The highly normalized xdwm consolidates and integrates data from multiple data sources. De-normalized summary tables and MOLAP cubes optimize query performance. 9 subject areas entities and 50+ business solutions. Broader and deeper than other models. The highly normalized xdwm is easily extended with new subtypes and attributes. Regular new versions covering industry developments and client feedback. M1 tool provides an import/export bridge to RDA, ERWin and Essbase server as well as model merge/compare and trace back functionalities. IBM provides dedicated software and helpdesk support. Deliverable on a wide-variety of platforms: hardware, OS, DBMS and ETL. Other Industry Models Other Models are not based on a classification model (taxonomy) or Information Framework. Other models are either 3NF OR star schema-based but rarely both. Data Models are not a core line of business for other vendors and R&D is often limited. Often subject areas and documentation are incomplete and there may be no business solutions. Other models are basically one-off solutions with no clear enhancement methodology. Not normalized enough to be extensible. Limited or no software for model management, generation or synchronization (i.e., model compare, merge or version control). No dedicated support for models and tools. Often completely proprietary based on the supported DBMS, OS or both. 14
15 15
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