Customer Master Data Management System (CMDM)

As part of Nissan's Customer Experience 2.0 (CE 2.0) - Making Confident Financial Decisions (MCFD) vision, a key initiative was the development of a robust Customer Master Data Management (CMDM) system. I served as the Architect for this project, responsible for designing and implementing a solution to create "golden records" of customer data and effectively manage CRM-related requests from loan customers. This CMDM platform was crucial for providing a unified and accurate view of customer information across various Nissan Financial Services systems.

The CMDM system was built using Talend MDM as its core technology, providing a comprehensive platform for data integration, cleansing, and master data management. The architecture was designed to integrate with various on-premise systems using a range of integration methods:

1. FTP Transfer: For batch data transfer from systems that supported file-based exchange.
2. Change Data Capture (CDC): For near real-time data synchronization, capturing changes in source systems and applying them to the CMDM.
3. Peer-to-Peer Integration: For direct, real-time communication between specific systems and the CMDM via APIs.
4. Enterprise Service Bus (ESB) Offerings: Leveraging existing ESB infrastructure for standardized and scalable data exchange via event bus.

The primary goals and functionalities of the CMDM system were:

1. Golden Record Creation: Establishing a single, accurate, and consistent view of each customer by consolidating data from multiple source systems. This "golden record" served as the authoritative source of customer information across the organization.
2. CRM Request Handling: Providing a centralized platform for managing CRM-related requests from loan customers, ensuring efficient and consistent handling of inquiries, service requests, and other customer interactions.
3. Data Quality and Consistency: Implementing data quality rules and processes to ensure the accuracy, completeness, and consistency of customer data within the CMDM.
4. Improved Data Accessibility: Making consolidated customer data readily accessible to authorized users and systems, facilitating better customer service, targeted marketing, and data-driven decision-making.
5. Data Stewardship: Implementing data stewardship practices to ensure the security, privacy, and quality of customer data throughout its lifecycle.
6. Data Lake Creation: Creating a data lake to store and aggregate customer data from various sources, providing a central repository for data analysis, reporting, and advanced analytics.
7. Other MDM Features: Implementing additional MDM features such as data lineage, master data governance, and business rules to enhance data management capabilities.

As the architect for the CMDM project, I was responsible for:

1. Architecture Design: Designing the overall architecture of the CMDM system, including data modeling, integration strategies, data governance processes, and the data lake architecture.
2. Technology Selection: Selecting Talend MDM as the core technology and defining the integration methods with various source systems.
3. Integration Strategy: Designing and implementing the integration strategy, including the use of FTP, CDC, peer-to-peer integration, and ESB offerings.
4. Data Modeling and Governance: Designing the data model for the CMDM, establishing data governance policies, and defining data stewardship practices.
5. Collaboration with Stakeholders: Collaborating with business stakeholders, IT teams, and other relevant parties to gather requirements, validate designs, ensure alignment with business objectives, and address data governance and security concerns.
6. Oversight of Implementation: Providing technical guidance and oversight during the implementation phase to ensure the successful delivery of the CMDM system.

The CMDM system played a vital role in realizing the CE 2.0 MCFD vision by:

1. Providing a single source of truth for customer data, enabling more personalized and efficient customer interactions.
2. Supporting streamlined CRM processes for loan customers, improving customer satisfaction and loyalty.
3. Facilitating data-driven decision-making related to financial services offerings and customer relationship management.
4. Enabling data-driven insights and analytics through the data lake and MDM capabilities.

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