IBM AnalyticsWhite paper

IBM Industry Models and IBM Master Data Management

Positioning and Deployment Patterns

• The Joint Value Proposition summarizes the scenarios in which IBM Industry Models and MDM accelerate projects and bring value.

• Positioning of IBM MDM and IBM Industry Models explains, by using the IBM reference architecture, where each product brings value, and how they work together.

• IBM Industry Models and MDM deployment options describes the different reasons for which IBM Industry Models are implemented, and how IBM Industry Models are used together with IBM MDM in implementing a solution.

• A comparison of IBM Industry Models and MDM discusses the similarities and differences in structure and content of IBM Industry Models and IBM MDM.

This document is intended for any staff involved in planning for or implementing a joint IBM Industry Models and MDM initiative within their organization, including IT Architects, Enterprise Architects and Business Analysts.

Although the value of implementing Master Data Management (MDM) solutions is widely acknowledged, it is challenging for organizations to realize the promised value. While there are many reasons for this, ranging from organizational alignment to siloed system architecture, certain patterns have been proven to dramatically increase the success rates of successful projects.

The first of these patterns, which is not unique to MDM projects, is that the most successful projects are tightly aligned with a clear, concise business value. Beyond this, MDM projects create challenges to an organization along several lines.

• MDM is a business application that acts like infrastructure. Organizations need to learn what this means to them and how they are going to adapt to it.

• Although MDM projects might not start with data governance, they quickly encounter it. MDM projects provide focus on what aspects of governance are required for the project’s value proposition.

• Mastering data implies that there are business processes concerned with establishing and maintaining the quality of that data.

• For MDM programs to be truly successful, they need to use a service-oriented architecture.

IBM’s experience is that industry-specific models can help organizations with the last three points, once they have identified the specific value proposition to be delivered by the project. This white paper explains what MDM is, what IBM® Industry Models are, and how the combination of the two can significantly improve the targeted value realization and can reduce project durations and overall costs.

This document contains the following:

2 IBM Industry Models and IBM Master Data Management

Introduction

Figure 1. MDM strategic components

IBM Master Data Management OverviewIBM InfoSphere® Master Data Management is the most complete, proven and powerful MDM solution with collaborative and operational capabilities.

Master data is the information about customers, products, materials, accounts and other entities that is critical to the operation of the business. But companies hold pieces of master data in many different applications, such as enterprise resource planning (ERP) and customer relationship management (CRM) systems. Each of those source systems creates and holds the data in its own unique way. As a result, information does not match from one system to the next. Critical data elements might be missing, duplicated or inconsistent. Furthermore, each department can operate only from within its own compartmentalized view.

IBM InfoSphere MDM software manages the creation, maintenance, delivery and use of master data, both to ensure that it is consistent and trustworthy, and to make it possible to see the data in an organization-wide context.

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By providing a single view of people, products, services and more, MDM enhances strategic decision making across an organization. The quality of that data shapes the decisions that are made and ultimately affects everything from customer relationships and regulatory compliance to business agility and competitiveness.

• Service-oriented architecture delivers functionality through intelligent, pre-packaged web services that can be used to seamlessly integrate MDM into existing business processes and technical architectures.

• Pre-built and extensible data models for any domain are optimized for MDM; an organization can import existing data models or build data models from scratch.

• Collaborative tasks allow workflows to be set up that reflect existing and new business processes, delivering a system that closely aligns with business practices.

• Business process management capabilities enable the implementation of policies and coordinate multi-step / multi-role workflows for data stewardship and data governance on-premises, in the cloud, and bridging between on-premises and cloud.

• Policy management ensures high quality master data using a quantitative, probabilistic approach to monitoring and enforcing policies.

• InfoSphere Governance Center allows business users, data stewards, and IT teams to collaboratively improve master data quality by resolving data quality tasks and creating master data in compliance with corporate governance policies.

• InfoSphere MDM Application Toolkit delivers business value rapidly with governance applications through pre-built blueprints and widgets for embedding within existing applications.

• Common matching and search engine employs advanced statistical techniques to automatically resolve and manage data quality issues using probabilistic or deterministic options.

Figure 2. Logical view of the MDM Hub

IBM InfoSphere MDM Standard and Advanced Editions (MDM Operational Server) deliver single, trusted and complete versions of critical data assets and their relationships to applications and users to support efficient operational business processes and strategic decision making. MDM helps clients in many industries share information across multiple systems to improve the services they provide to patients, citizens and customers.

IBM InfoSphere MDM Collaborative Edition (MDM Collaboration Server) manages master product data to maintain a single view of product information for use throughout an organization and as part of a comprehensive MDM strategy.

IBM InfoSphere MDM Reference Data Management Hub (RDM) is a robust MDM solution for centralized management and distribution of reference data across the enterprise. (Reference data is static data, such as code tables, used to classify business entities – for example, salutation, gender, country code). It provides the governance, process, security and audit control for managing reference data as an enterprise standard, resulting in fewer errors, reduced business risk and cost savings.

IBM InfoSphere Big Match for Hadoop helps analyze large volumes of structured and unstructured data to derive deeper customer insight on a Big Data platform.

IBM Industry Models OverviewIBM Industry Models provide predefined data model industry content for banking, financial markets, telecommunications, healthcare, insurance, retail and energy & utilities. The main components of the data model are:

Business Terms

Business terms define industry concepts in plain business language, with no modeling or abstraction involved. Business terms have a standard set of properties and are organized by business category. Clearly defined business terms help standardization and communication within an organization.

Supportive Content

Supportive Content represents data elements in the language of a given source requirement. For example, requirements such as Health Level 7 (HL7), which is the standard series of predefined data formats for packaging and exchanging healthcare data in the form of messages that are transmitted between disparate IT systems, or BASEL, which defines the capital requirements for banks.

Analytical Requirements

Analytical Requirements reflect the most common queries and analyses for business performance measurement and reporting. They help with the rapid scoping and prototyping of data marts, which provide a subject-specific analytical layer in a data warehouse solution.

4 IBM Industry Models and IBM Master Data Management

Business Data Model (BDM)

The Business Data Model is the first point at which the various business requirements are brought together and modeled in an entity relationship format. It helps organizations to perform the initial modeling of their business requirements and understand the various constraints, relationships and structures that can be implied in their business requirements.

Atomic Warehouse Model (AWM)

The Atomic Warehouse Model is a logical, specialized model that is derived from the BDM. It is optimized as a data repository, which can hold long-term history, usually across the entire enterprise in a flexible manner.

Dimensional Warehouse Model (DWM)

The Dimensional Warehouse Model is a logical model that is derived from the BDM and is an optimized data repository for supporting analytical queries. This repository holds data to meet the needs of business-user-required analyses.

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Figure 3. IBM Industry Model components

Analysis Process Model (APM)

The Analysis Process Model provides the initial Business specification of processes, which is used to underpin the initial analysis activities in determining the optimum subset of processes for a Project, from a business perspective.

Orchestration Process Model (OPM)

The Orchestration Process Model Provides the design level technical specification of processes, which forms the basis for any downstream implementation of executable processes.

In all industries, the Business Vocabulary provides a common semantic reference point across the different Data, Process and Services domains. All of the models in these three different technical domains (analytical, process and service) are mapped to the equivalent business terms in the Business Vocabulary.

In the case of Banking, Financial Markets and Insurance, IBM Industry Process and Services Models are also available. This extended landscape consists of the following model components:

Business Object Model (BOM)

The Business Object Model is the first point at which the various business requirements are brought together and modeled in UML. The BOM is essentially the UML equivalent of the BDM and performs the same role and provides technology independent class models that enable traceability between automated business process requirements and downstream SOA IT analysis representation.

Interface Design Model (IDM)

The Interface Design Model provides a design for the development of components, types, interfaces, and data transfer objects for an enterprise-wide business services-based architecture.

Services Design Model (SDM)

The Services Design Model provides a design for the development of participants, service interfaces, and messages appropriate for an enterprise-wide business services-based architecture.

Figure 4. How IBM Industry Model components relate to each other in an analytics landscape

6 IBM Industry Models and IBM Master Data Management

The Business Terms that are provided by IBM Industry Models provide a canonical set of data elements that are expressed in the language that is commonly used by business users. With the Business Terms as a starting point, all of the information elements in the organization (whether owned by MDM or other systems) can be understood, related to other elements, and managed.

Industry Models also help accelerate the focus of a project. When delivering an analytics project, for example, the Analytical Requirements provide the requirements for a set of KPIs that will be used to measure progress towards achieving business value. The Analytical Requirements identify the business objects required, which can then be traced down to the critical attributes within logical and physical systems. Specific data governance rules can be created based on the importance of each attribute having one of a defined set of values.

IBM Industry Models also provide a logical data structure of the objects in scope for a project. The result is that the project team obtains a more complete description of what will be involved in delivering the business value, with a logical data model helping them organize how these objects are related, and complete definitions with examples to ensure that there is a common and accurate definition of the objects themselves.

The benefits of using IBM Industry Models to help drive the data governance process are:

• A business-led understanding of the information within the organization, bringing together a semantic map of all information elements within the organization, whatever their role in the organization.

• Significantly reduced time to describe the required business objects and underlying attributes.

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The provision of a broader enterprise context is a fundamental overall value proposition for using the IBM Industry Models with IBM MDM. This wide cross-LOB scope of IBM Industry Models providing semantic and structural consistency is complementary to the deep focus that MDM applications provide to specific subject areas such as Customer and Product.

As mentioned earlier, the IBM Industry Models help MDM projects along three strategic lines:

• Although MDM projects might not start with data governance, they quickly encounter it. MDM projects provide focus on what aspects of governance are required for the project’s value proposition – the area of Data Governance.

• Mastering data implies that there are business processes around establishing and maintaining the quality of that data – the area of Business Processes.

• For master data programs to be truly successful, they need to use a service-oriented architecture

Addressing the Main Business IssuesLet’s dive down more deeply into each of the 3 main MDM project issues that are mentioned above, and the benefits that a well thought out and exercised model brings:

Data Governance

While there is a common understanding of the need for data governance, most companies encounter challenges figuring out where to start. In an MDM project, the value proposition of the first project helps bring focus from a broad topic with thousands of attributes to a much more focused and manageable set. Some of these attributes might be owned by MDM and some by other systems or the Enterprise Data Warehouse (EDW).

Joint Value Proposition

• Complete definitions of both what it takes to deliver business value, as well as the supporting objects, provide focus on what is important, further reducing both high-level design as well as testing.

• Complete definitions also reduce or eliminate discovery – which can often happen late during the testing process, and which can add months to a project.

• The ability to generate both the supporting EDW structures as well as specific star configurations required for a focused set of analytics.

Business Process

One of the keys to understanding and mastering data is knowing exactly what the business processes are which create and change that information – in other words, optimized business processes that support the complete lifecycle of the information within an organization. IBM Industry Process Models provide ready-made processes and services that are constructed with customer focus, without the need to reinvent from scratch. The integration and consistency of the business processes provide extensive re-usability of activities and processes, and translate into less process maintenance and reduced training costs, while enabling flexibility in the workforce. The customizable generic process templates enable an organization to meet its specific project requirements.

Service Oriented Architecture

A Service-oriented architecture (SOA), as a common basis for integration and as a means of structuring large-scale software architectures, is rapidly becoming the backbone of the modern financial institution. An SOA can increase the speed of business changes, improve business efficiency and performance, as well as protect the privacy and security of critical information assets. An SOA enables IT to align more tightly with business strategies in a cost-effective manner and in a secure and managed integration environment.

A key factor underpinning successful SOA is a common, enterprise-wide description of business concepts and processes of interest to a financial institution. Without this common language, any attempt to support a consistent and flexible architecture will more than likely fail. IBM Industry Services Models provide this common language and also support a complete and unambiguous description of the business services that are required to support the organization. The Service Models enable the efficient and accurate gathering of requirements, and guarantees the consistency of definitions with a single integration effort or across multiple projects.

The Service Models are tightly coupled with the Process Models, describing the underlying services that support these processes at run time. Using the Service Models, business concepts can be traced from analysis level through design level refinements to actual component and message definitions that provide a quick start for the specification of common services within the organization.

To summarize, the synergies between IBM Industry Models and InfoSphere MDM are:

• IBM Industry Models provide a set of business terms which provide a business context for the information that is mastered by InfoSphere MDM.

• Analytical Requirements provide the business requirements for areas of analysis for which the business community requires support. Each element in these templates is related to elements in an EDW or data lake/reservoir design, and can be related to elements of information that are mastered by using IBM InfoSphere MDM.

• IBM Industry Process Models provide a business context for the information that is created and updated by business operations, and is maintained by IBM InfoSphere MDM.

• IBM Industry Services Models provide a linkage from business processes that are defined in the process models, to the underlying services that can be provided by IBM InfoSphere MDM –allowing a translation of the “to-be” best practice business processes into implemented SOA-based services for master data.

8 IBM Industry Models and IBM Master Data Management

The IBM Analytics LandscapeFigure 5 shows the relevant subset of a possible overall Analytics Landscape. This landscape will be used to frame the relative placement of the various IBM MDM and IBM Industry Model components that are described in this document, and is known as the IBM Data Reservoir Reference Architecture. You can find additional information on IBM Data Reservoir in the IBM Redbook Designing and Operating a Data Reservoir.

IBM MDM PositioningThere are three main IBM MDM components that need to be positioned with the IBM Industry Models in the context of a typical Data Reservoir landscape. These three components are:

• Virtual MDM

• Physical MDM

• MDM services

The specific positioning of these MDM capabilities are shown in Figure 6, using a subset of the standard components in the IBM Data Reservoir Logical Architecture. The Virtual MDM capability is considered part of the Information Views. The Information Definitions of simplified subsets of information that is stored in the data reservoir repositories. These views are created with the information consumer in mind.

The Physical MDM capability is part of the Asset Hub, which is defined as slowly changing operational master data (information assets) such as customer profiles, product definitions and contracts. The Asset Hub provides authoritative operational master data for the service interfaces, real-time analytics and for data validation in data ingestion. It is a reference repository of the operational MDM systems but can also be extended with new attributes that are maintained by the reservoir.

The MDM Services are positioned within the Services Interfaces component and they provide a standard programmable interface for accessing the data that is stored in the MDM Asset Hub.

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Positioning in an Analytics Landscape

Figure 5. IBM Analytics Landscape

Figure 6. Positioning on IBM MDM in the IBM Analytics Landscape

Figure 7. Deployment paths for IBM Industry Models

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IBM Industry Models and IBM MDM MappingsIBM provides a series of predefined attribute level mappings between the relevant components of IBM Industry Models, the MDM physical data model and the MDM Services Layer. These mappings provide an indication of where the same or equivalent data and services elements exist between IBM Industry Models and IBM MDM. Shown in Figure 8. The three different types of mappings are shown in the above diagram. These mappings are intended to provide an accelerator to clients wanting to have a combined deployment of IBM MDM and runtime artifacts that are derived from IBM Industry Models. The three types of mappings are:

1 Mapping between Business Terms and the MDM physical data model. This mapping would be useful in establishing an overall information governance based on a common glossary or taxonomy of business terms that includes linkage to the physical MDM components, in addition to possibly other components.

2 Mapping between the Atomic Warehouse Model and the MDM physical data model. This mapping is intended to provide guidance to clients wanting to establish an overall ETL layer that includes IBM MDM and an IBM Industry Models-derived Information Warehouse as target data structures.

3 Mapping between the Service Design Model and the MDM services layer. This mapping is intended to provide guidance on possible linkage between IBM Industry Models-derived runtime services and the MDM Services layer.

IBM Industry Models PositioningTypically IBM Industry Models are design-time artifacts and are used to underpin the related development activities. In general, a number of IBM Industry Model components deploy into this physical landscape. Figure 7 outlines the main deployment paths for IBM Industry Models

1 The Business Vocabulary content, usually stored in InfoSphere Information Governance Catalog are deployed into the Catalog component.

2 The Atomic Warehouse Model provides a key design point for the overall logical data warehouse and so deploys to a number of components.- The traditional relational Information Warehouse component. - The usually Hadoop-based Deep Data component- Potentially used to deploy Operational History

3 The Dimensional Warehouse Models would provide much of the design content for the Reporting Data Marts. In addition, where a client is looking to deploy a Kimball dimensional warehouse they might also use the Dimensional Warehouse Models to deploy a dimensional variant of the information warehouse.

4 The Service Design Model provides the basis for enforcing a common standardized basis for the deployment of the Services that are used by the Real-time Interfaces.

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Figure 8. Mappings between IBM Industry Models and IBM MDM

12 IBM Industry Models and IBM Master Data Management

This chapter explains some typical use cases in which IBM Industry Models and IBM MDM are deployed – and why those use cases are of benefit.

IBM Industry Models Deployment Options

Business Vocabulary

In this scenario, the customer uses part or all of the Business Vocabulary component of IBM Industry Models to provide the central semantic reference point for multiple projects. In addition, customers might turn to using the Business Vocabulary in the face of the growing and more diverse nature of the overall runtime landscape.

In this case, some or all of the Business Vocabulary is deployed in the Catalog component, usually in the IBM InfoSphere Governance Catalog tool.

A significant advantage of this tool is that this is used as the source of business terms both at design time and run time. The Business Vocabulary can be mapped to the various physical assets and be used to underpin data lineage activities.

Optionally, the Business, Atomic and Dimensional models can also be loaded into the Catalog to provide further context or lineage.

Data Warehouse Deployment

For many customers, this is a core deployment use case of IBM industry data warehouse models. It relates to the use of the data warehouse design models (Atomic Warehouse and Dimensional Warehouse) to deploy the required runtime data warehouse artifacts.

In this deployment scenario, a client can choose to adopt either an Inmon relational approach in which case they will focus their attention on the Atomic Warehouse Model. They can also use the Dimensional Warehouse Model to provide a downstream layer to support any user interaction.

Alternatively the client might choose to adopt a Kimball approach and center their development on the Dimensional Warehouse Model and deploy a single dimensional warehouse layer. This has the advantage of being a simpler deployment option but might sacrifice some of the flexibility of the Inmon approach

Another consideration that might guide deployment choice is the advent of Hadoop based Deep Data structures being used to augment traditional the Information Warehouse. Currently, the Atomic Warehouse Model is validated for deployment to the IBM BigInsights Hadoop solution.

This data warehouse deployment option can also be used with the Business Vocabulary deployment option.

Deployment Options

Figure 9. Business Vocabulary deployment

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Services Deployment

The third deployment option that is relevant to IBM MDM is the deployment of SOA Services. Traditionally this deployment option occurs where the UML interface Services Design Model in a tool like IBM Rational Software Architect is used as the basis for the generation of the relevant services run-time artifacts such as XSD, WSDL, etc.

Combined IBM Industry Models and IBM MDM Deployment

OptionsThe possible combined deployment of the IBM Industry Models and IBM MDM on this overall landscape can be described by the following:

• Integrated Data Governance

• Integrated Services deployment

Combined Governance of MDM and IBM Industry Models derived

components

Both IBM Industry Models and IBM MDM products are key to providing some of the core components of the centralized set of data reservoir repositories. With that in mind, the ability to enforce a workable approach to the overall governance of these assets is critical to the ongoing long-term exploitation of these assets.

Exploiting the pre-built integration between IBM Industry Models and IBM MDM is important in ensuring that a combined approach to this overall information governance landscape is achieved. Figure 12 outlines how the main components of IBM MDM and those derived from IBM Industry Models can be considered as part of an integrated set of governed assets.

The core to this is the Catalog, the location in which all of the metadata that is needed to describe the various repository components is stored. The catalog can provide a single viewpoint of all of the components.

1 The Catalog itself can store a layer of Business Terms, where the overall environment is described in the language of the business and in a means that is independent from the specific technologies. The catalog will also store detailed metadata that describes each of the relevant data reservoir components and how they relate to each other.

2 The linkages between the Catalog elements and the MDM Asset Hub. This would be heavily influenced by the mappings between the Business Terms and the MDM physical model.

Figure 10. Data Warehouse deployment

Figure 11. Services deployment

14 IBM Industry Models and IBM Master Data Management

3 In this landscape, where the Information Warehouse and any associated Reporting Data Marts are derived from the IBM Industry Models, then such physical artifacts would also inherit any linkages that existed between their equivalent logical models and the Business Terms in the Catalog.

4 Potentially some deep data. In some cases such stores can be derived from IBM Industry Models, in which case these artifacts might also be included in the overall set of components subject to such an information governance approach.

In addition to providing the metadata of the components, the catalog should also provide a view of any relationships that exist between the various components.

This linkage between the Business Term, the Data Warehouse Model(s) and the MDM physical model enables a common information governance approach to be built out including IBM Industry Model derived assets and IBM MDM components.

Model example: Implementing a Business Intelligence solution for

Customer Profiling

As part of their customer intelligence solution, Bank ABC wants to understand their customer base.

The business analyst consults the content of the Analytical Requirements. Under the focus area “Relationship Marketing”, they find the Analytical Requirement “Individual customer profile”.

Figure 12. IBM MDM and Industry Model components as part of an integrated set of governed assets.

Figure 13. Example - Individual Customer Profile

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The Analytical Requirement Individual Customer Profile includes a number of measures and dimensions that are used to analyze the demographics of the financial institution’s customer base:

This provides a starting point for designing a data mart to support analysis:

Let’s take an example of Gender to see where this can be mastered.

The mappings to the Atomic Warehouse show where in the EDW design support for Gender can be found:

The corresponding MDM attribute can be found by consulting the MDM/Industry Data Model for Banking (Banking Data Warehouse) mapping spreadsheet, which is available to licensed customers of both MDM and IBM Industry Model products:

To summarize, this use case shows:

• Banking Data Warehouse models a source of analytics design.

• The ability to find (and customize if required) the logical structure to support the analytics.

• The ability to determine how to support elements of the analysis in an EDW.

• The ability to find the master data that will provide the source for the analysis, by using the MDM/Banking Data Warehouse model mappings.

Figure 14. Example - Measures and Dimensions

Figure 15. Example - Designing a data mart

Figure 16. Example - Gender

Figure 17. Example - MDM mappings

16 IBM Industry Models and IBM Master Data Management

Combined MDM and IBM Industry Models services deployment

The IBM MDM product also includes a services layer that provides a standard interface to enable a consistent and robust access to the MDM data by other applications. Given that IBM Industry Models for Insurance and Banking include models that would be used to enable the generation of a services layer typically for use by Systems of Record and Systems of engagement, then a services-related deployment pattern is possible.

IBM Service Design Models can provide the basis for the services layer both for the Systems of Record and Systems of Engagement (item (1) in the diagram) as well as providing the services layer for certain data artifacts in the System of Insight (2).

The MDM Services Layer and any services that are generated from IBM Industry Models can be used to together as part of an overall ESB environment.

Alternatively, IBM MDM Services could be adapted to use service layer definitions from IBM Industry Models using MDM Adaptive Service Interface functionality. MDM provides the ability to map externally defined service interfaces to internal MDM service and business object definitions. In essence, MDM could be “taught” to “speak” the language of the Service Design Model for subset of services that are used in MDM deployment.

The approach of using Adaptive Service Interface (ASI) for adapting MDM interfaces to adhere to IBM Industry Model definitions can provide some performance benefits over the approach of using an ESB to perform the same mapping in cases when several sequential calls to MDM is required for full business function. Solution developers can create composite transactions using MDM business proxy capabilities.

Model Example : Implementing a Business Process using the IBM

Industry Models Process and Service Model and MDM services

As part of their commitment to enterprise process engineering, and with a focus that is driven by new regulatory requirements in this area, Fund Manager Company XYZ has decided to examine their customer onboarding procedures.

In order to find the relevant processes to examine, the Value Chains are reviewed. The Value Chains present Line of Business functions that are supported by a set of long-running business processes.

In this case, KYC and Account Opening is the most relevant:

Figure 18. Example - Services deployment

Figure 19. Example - Value Chains

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This provides the context for the process modeler to home in on relevant processes, including “Administer IP Onboarding”. The process modeler opens the Analysis Process Model in Rational System Architect (RSA), for example, and examines the process:

For each of the activities in the process workflow diagram, the model provides an understanding of the data inputs and outputs, and the end to end process flow. The company can choose to customize the process elements, reviewing their granularity and potentially introducing new process activities or subprocesses.

A key element of analyzing the business processes in the APM is determining which activities are service candidates, i.e. are candidates for automation – these are the process steps that can ultimately be supported by a set of common services, such as provided by IBM InfoSphere MDM.

For Service Candidate activities, the next step is to identify the relevant Service Capability Operation in the Business Object Model (BOM), which is the analysis-level services model.

Taking “Retrieve Full Customer Details” as an example, the corresponding BOM Service Capability Operation, of the same name, is found in the “Involved Party Management” Capability: And, examining the Relationships that the “Retrieve Full Customer Details” Operation has, shows the association in the design-level Service Design Model (SDM):

Figure 21. Example - Retrieve Full Customer Details

Figure 22. Example - Service Design Model

Figure 20. Example - Process

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Following the link from the BOM Operation leads to the “retrieveFullCustomerDetails” SDM Service Operation, under the “IInvolvedPartyManagement” ServiceInterface:

The corresponding MDM attribute can be found by consulting the MDM/BPS mapping spreadsheet.

Model Example: Mapping the Service Design Model to MDM

services

Building further on the example that is mentioned in previous section, solution developers can use MDM Adaptive Service Interface feature to map “recordInvolvedParty” service interface that is defined by IBM Industry Models to addParty MDM service. An example of such mapping is provided as part of MDM distribution package.

To summarize, this use case shows:

• IBM Industry Model for Banking as a source of process and service analysis

• The ability to find (and customize if required) the relevant model elements in scope

• The ability to find the master data that will provide the source for the analysis, by using the MDM/IBM Industry Model mappings

Figure 23. Example - MDM Mappings

Figure 24. Example - Service Operation Figure 25. Example - Service Design Model mapping

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Scope of the MDM and IBM Industry ModelsThe IBM InfoSphere MDM data model represents the persistence store on which MDM services operate, retrieving data through services and updating this data through services. It is structured to meet MDM needs, which are best provided through the identification of information domains. MDM defines three major domains of Party, Product and Account, which are represented in the DOMAIN model.The following shows the main entities that are included in the Party Domain: Both the banking and insurance IBM Industry Models support the three domains of MDM. In the case of insurance, since the development of MDM was highly influenced by the IMB Industry Models for Insurance, the naming of concepts are largely similar. In the case of banking, there is also a high level of overlap in these domains, although the names might differ – for example, IBM Industry Models for Banking uses “Involved Party” for MDM’s “Party”.

The main difference in domain coverage is in the breadth of coverage of IBM Industry Models. The scope of IBM Industry Models is to provide an enterprise-wide view of all of the information in the organization, and thus to integrate the potentially many operational master systems that exist in a given organization. There might be a different master for ledger information, and both of these sources are integrated by using IBM Industry Models. On the other hand, MDM masters only aspects of Party, Agreement and Product that are common across multiple business processes in organization.

Another difference in IBM Industry Models is the approach to data quality.

MDM ensures information about the same party that is updated simultaneously from potentially a large number of consuming applications will be cleansed and de-duplicated inside MDM using sophisticated probabilistic matching engine, therefore always ensuring the best quality.

As a data warehouse model, IBM Industry Models assume a level of cleansing before data is accepted into the warehouse database, so there is, by design, any inbuilt tolerance of duplication.

Data Model Similarities and DifferencesMDM represents both a logical and a physical model; the physical model needs to be stable and predetermined as a basis for data retrieval through services, optimized for operational access pattern. IBM Industry Models are purely logical models, which are open to customization, and can be implemented on a variety of both traditional DBMSs and less traditional environments, such as Hadoop.

A Comparison of IBM Industry Modelsand IBM MDM

Figure 26. Main entities in the Party domain

20 IBM Industry Models and IBM Master Data Management

One difference that ensues from this is the approach to customizations to the model. In the case of MDM, there are two main approaches – hard persistence involves changes to the model and underlying database, with potential changes being required to associated services. The soft persistence strategy involves the use of Specs and XML metadata to provide an interpretation of customizations with no physical changes being required. In the case of IBM Industry Models, since this is a logical model, and is typically customized before being physically implemented, there is no soft persistence strategy.

Some of the MDM elements are internal application administration and management that is related and as such would not be stored in a data warehouse. These elements are not required in a mapping between the models.

There is a similar approach to a number of modeling patterns between both products, including the use of surrogate keys, the support of business history using start and end date attributes, and the use of Code tables to store reference data.

At the package level, the following represents the similarities between MDM and banking IBM Industry Models.

MDM Package BDW Package

Party Involved Party

Product Product

Account Arrangement

<Party> Party Events Event

<Prduct/Account> (Term & Conditions)

Condition

At the package level, the following highlights where there is overlap between MDM and IBM Industry Data Models for Insurance (IIW) and, in additional, areas of content support in insurance that is not contained in MDM

MDM Package IIW Package

Product Product

Account Agreement

<Partial “Account”> Account and Fund

<Partial Account/Product> (Term & Conditions)

Assessment and Condition

<None> Actuarial Statistics and index

<Account> Claim Summary Claim

<Party> (Party Events) Event

<Partial Account> (Billing Summary

Financial Transaction

<None> Legal Action

<Partial Party> (Income Source) Money Provision

<{Partial Account> (Claim Summary/Contract Component Holdings)

Physical Object

<Party> (Macro Roles) Registration

<None> Standard Text and Communication

The following highlights by example elements in MDM that are not contained within IIW:

• The approximately 1100 MDM code tables that are listed have not been mapped. The reason being that the code tables are reference data and are not used for persisting data. They relate to the values available for the corresponding table attribute.

• Any MDM elements that are defined as a metadata component, for example CRITICALDATAELEMENT, have not been mapped as IIW does not support this type of data construct.

• There is limited support for the MDM concept of ‘Rules of Visibility’ in IIW and again limited mapping to support that area. An example of this is ENTITLEMENTCONSTRAINT / ENTITLEMENT which has not been mapped to any construct in IIW

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September 2015

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Summary

IBM MDM provides a solution for ensuring that the critical core data that is referenced and updated by multiple systems within an organization is appropriately governed. It provides persistence structures and services to allow these core elements to be managed centrally and effectively.

IBM Industry Models provide a context of this core information within a logical map of all of the concepts that an organization must manage. They also provide an analytical reason for the use of the information that is managed by IBM MDM. IBM Industry Process and Service Models provide the business context for the need for IBM MDM services.

Together IBM MDM and IBM Industry Models provide analysis and implementation of both core operational information and the analytical structures that will allow the business to be managed.