Master Data Management - Design Principles and Architecture - Practitioner’s Framework: Part-I

Part-1 of this article talks about the underlying design principles and logical architecture

Design Principles

Encapsulation

The MDM solution will provide the ability to decouple information from enterprise applications and processes to make it available as a strategic asset for use by the enterprise. This is a fundamental concept of Information on Demand founded upon Service Oriented Principles to deliver information at the right time in the right context to the right application or user. Components in a loosely coupled system are less constrained to the same platform, language, operating system, or build environment.

Scalability

The MDM solution will provide the enterprise with an authoritative source for master data that manages information integrity and controls the distribution of master data across the enterprise in a standardized way that enables reuse and scalability. The primary motivation for this principle is to centralize the management of master data to reduce data management costs and improve the accuracy and completeness of that data.

Flexibility

The MDM solution will provide the flexibility to accommodate changes business requirements and regulations and support the addition of new master data. This improves the ability of a business to quickly respond to business changes that may require the addition of new master data elements or changes to existing master data.

Data Integrity and Privacy

The MDM solution will be designed with the highest regard to preserve the ownership of data, integrity and security of the data from the time it is entered into the system until retention of the data is no longer required. The objective of this principle is to ensure that core business data that is critical to the success of the enterprise will be secure and to comply with privacy laws and regulations.

Interoperability

The MDM solution will be based upon industry-accepted open computing standards to support the use of multiple technologies and techniques for interoperability with external systems and systems within the enterprise. This will guide development of the architecture to remain open and flexible so it can easily integrate with a variety of vendor software that may already exist within the enterprise and any future unknown technologies.

Reusability

The MDM solution will be based upon an architectural framework and reusable services that can leverage existing technologies within the enterprise. This principle guides the architectural decisions to leverage existing investments in technologies such as those that facilitate connectivity and interoperability or information integration where it makes sense in order to implement a MDM Solution.

Modularity

The MDM solution will provide the ability to incrementally implement an MDM solution so that a MDM solution can demonstrate immediate value.

Logical Architecture

Services and Repository Logical Blocks

01- Interface Services support a consistent entry point to request MDM Services through techniques such as messaging, method calls, web services, API integration using micro-services and batch processing. The same MDM service should be invoked during batch processing that may be requested as part of a transaction in order to maintain and apply consistent business logic

02- Lifecycle Management Services manage the lifecycle of master data, provide CRUD (create, read, update, and delete) support for master data managed by the MDM System, and apply business logic based upon the context of that data. Data Quality Management Services are called by Lifecycle Management Services to enforce data quality rules and perform data cleansing, standardization, and reconciliation. MDM Event Management Services are called to detect any actions that should be triggered based upon business rules or data governance policies.

03- AI enabled Hierarchy and Relationship Management Services manage master data hierarchies, groupings, and relationships that have been defined for master data. These services may also request Identity Analytics Services to discover relationships, such as those between people that are not obvious, and then store that information in the MDM System.

04- MDM Event Management Services are used to make information actionable and trigger operations based upon events detected within the data. Events can be defined to support data governance policies, such as managing changes to critical data, based upon business rules or time and date scheduled.

05- Authoring Services provide services to author, approve, manage, customize, and extend the definition of master data as well as the ability to add or modify instance master data, such as product, vendor, and supplier. These services support the MDM collaborative style of use and may be invoked as part of a collaborative workflow to complete the creation, updating, and approval of the information for definition or instance master data.

06- Data Quality Management Services validate and enforce data quality rules, perform data standardization for both data values and structures, and perform data reconciliation. These services may request Information Integrity Services that are available from the Information Integration Services architecture building block

07- Base services are available to support security and privacy, search, audit logging, and workflow. Base services can be implemented to integrate with common enterprise components that support workflow, security, and audit logging. Some of these could be automated using RPA tools such as Automation Anywhere, Blue Prism, UI path etc.

08- The Master Data Repository consists of master data, both instance and definition master data, metadata for the MDM System, and history data that records changes to master data. MDM Services can also be used to maintain and control the distribution of reference data that should be maintained at the global level for an organization.

09- Information Integration Services provide Information Integrity Services, ETL services, and EII services for federated query access to structured and unstructured data distributed over disparate data sources.

10- Information Identity (& Integrity) Services include data profiling, analysis, cleansing, data standardization, and matching services. Data profiling and analysis services are critical for understanding the quality of master data across enterprise systems, and for defining data validation, data cleansing, matching, and standardization logic required to improve master data quality and consistency. MDM Data Quality Management Services can request Information Integrity Services to standardize, cleanse, and match master data updates received by the MDM System from a business system.

11- Identity Analytics component is a building block of Analysis & Discovery service – it is recommended that you deploy this only in the scenarios when you want to determine the true identity of a person. These services can also be used to discover non-obvious relationships between people, such as those that are part of the same household but have different names and address information, and between people and organizations.

MDM Hierarchy and Relationship Management Services can request these services and then store the results in the MDM Data Repository. In order to identity Analytics Services to effectively discover relationships and a person’s true identity, it may be necessary to load and analyze data from external data sources along with data from within the enterprise. Information Integration Services can be used to load data into the Identity Analytics component.