Master Data Management (MDM) in the Cloud Era

Gartner Defines Master Data Management (MDM) as

a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts.

In the era of cloud and generation driven by data, organizations are turning to master data management (MDM) to address the complexities and demands of modern data environments. MDM strategies are increasingly integrated into cloud architectures to achieve scalability, flexibility, and advanced data governance.

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A key aspect of this adoption is the use of centralized data repositories, such as ‘Golden Records.’ These repositories ensure that the most accurate and up-to-date information is accessible across the organization, maintaining data integrity, enabling real-time data access, and supporting better decision-making processes. Organizations leverage AI and machine learning technologies to enhance data consistency across multiple systems and platforms.

Each organization’s journey to the cloud is unique. While agility, nimbleness, and cost benefits are significant factors, businesses also evaluate the maturity of cloud-based solutions from a data security and capability standpoint. Ensuring data security and compliance with regulations is crucial for businesses handling sensitive information.

An effective cloud-based MDM solution must meet business demands for speed and agility while providing enterprise-class functionality and scalability.

MDM and Cloud Computing: A Synergistic Relationship

Cloud MDM is confined to managing and governing the master data of an enterprise. This innovative solution combines the principles of traditional Master Data Management with the power of cloud technology advantages in an effort to help businesses efficiently centralize, maintain, and distribute their master data assets.

It serves as a guardian for the most critical data of every organization, such as customer, product, supplier, and employee information. It makes this data consistent, accurate, and easily accessible for use within different business applications.

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Importance of Cloud MDM

In contrast to traditional MDM, Cloud MDM offers several advantages in flexibility, scalability, and accessibility. With data in the cloud, an organization can respond rapidly to changing data needs, allow remote work, and permit data integration with other cloud-based services.

This section will help organizations transition from traditional MDM to Cloud MDM. The article further describes the key features and benefits of Cloud MDM and how it differs from cloud-based and on-premises solutions, as well as addresses some of the crucial security and compliance considerations.

Three major Benefits of Cloud-Based Master Data Management Solutions

1. Cost Efficiency and Flexibility:

Cloud-based MDM offers flexible plans that match business needs, simplifying the discovery, creation, and management of critical data relationships.

2. Quick Implementation and Scalability:

These solutions integrate seamlessly with existing systems, allowing for easy scaling of storage, processing capabilities, and licensing limits without the need for onsite servers, enhancing operational agility.

3. High Security:

While storing sensitive data outside company firewalls can be concerning, cloud-based MDM systems typically run on platforms like Microsoft Azure or AWS, which offer top-tier security resources otherwise unaffordable for individual companies.

How is Cloud MDM different from Traditional MDM?

Key Components of Cloud-Based MDM Solutions

Cloud MDM solutions are an all-in-one package of features and functionalities, including data integration. The solutions offered house data from various sources, be it internal or external, into one central platform. This is achieved to ease the process of data consolidation.

• Data Cleansing: This is one feature that can clearly identify and correct the problems or inconsistencies in data to assure its accuracy and completeness.
• Data Governance: These solutions offer an enterprise-wide robust framework for the management of data in compliance with regulations and policies.
• Data Quality Management: Cloud MDM provides tools and workflows to hold up high-quality data for organizations to ensure consistency, accuracy, and timeliness.
• Data Analytics: Such solutions offer insights and analytics that will enable organizations to drive data-driven decisions.
• Workflow Management: Cloud MDM provides the tools and workflows to manage the data management process efficiently and effectively.
• Security: Cloud MDM securities are enhanced using data encryption, firewalls, and customer authentication to prevent sensitive data from cyber threats.

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Ensuring Security and Compliance in Cloud Master Data Management

When implementing cloud master data management (MDM), security and compliance are paramount. Here are key considerations to ensure robust security and adherence to regulatory standards:

• Data Privacy: Cloud MDM solutions often store sensitive information, including customer and financial data. Ensuring data privacy involves storing this data securely and complying with regulations like GDPR and CCPA. Cloud MDM solutions typically include security features such as encryption and data masking to protect sensitive information.
• Access Control: Limiting access to sensitive data to authorized users is crucial. Cloud MDM solutions offer granular access control mechanisms, allowing administrators to set permissions at the individual user or group level, ensuring only necessary personnel can access sensitive information.
• Regulatory Compliance: Organizations must adhere to industry-specific and regional regulatory requirements. Cloud MDM solutions should support compliance with relevant regulations, providing necessary features and documentation to meet these standards.
• Data Residency: Certain regulations may require data to be stored within specific geographic regions. Cloud MDM solutions should enable organizations to choose the data storage location, ensuring compliance with data residency requirements.
• Data Backup and Recovery: Robust data backup and recovery capabilities are essential for protecting data from loss due to hardware or software failures, natural disasters, or other unforeseen events. Cloud MDM solutions typically offer strong backup and recovery features to ensure data integrity and availability.
• Vendor Security: Relying on third-party cloud service providers necessitates ensuring that they have strong security measures against data breaches and cyber-attacks. Reviewing the provider’s security and compliance certifications ensures they meet industry standards and can be trusted with sensitive data.

Top Master Data Management Tools 

IBM

Syniti

Teradata

SAS

Reltio, Inc.

Plauti data management

Microsoft Azure

Best Practices for Cloud Master Data Management

Cloud computing has gained significant attention since Amazon Web Services (AWS) launched in 2006. Amazon has led the shift in product and service delivery, but its dominance now faces challenges from Microsoft’s and Google’s aggressive cloud computing platforms.

Many organizations have unique strategies for their cloud journeys, often choosing different cloud providers. From a master data management (MDM) standpoint, companies seek options that provide agility, flexibility, and cost benefits, while also ensuring the solution’s maturity in terms of capability and data security.

While many cloud-based MDM solutions offer speed and flexibility, they often lack tested, enterprise-class functionality and scalability. This can be concerning for businesses needing to comply with regulations that require robust data protection.

Here are areas every organization should consider when embracing a cloud-based MDM solution:

1. Don’t Compromise on Completeness –

Due to the immaturity of many cloud MDM solutions, businesses often create comprehensive MDM solutions using tools from multiple vendors. A complete cloud-based solution increases efficiency by offering all capabilities in one place, allowing organizations to focus on deriving business value from MDM. An ideal cloud solution should combine data catalog, data integration, data quality, data enrichment, and business process management into a single offering. Companies like TELUS, Wolters Kluwer, and Coca-Cola leverage end-to-end MDM solutions on the cloud to ensure success.

2. Data Security Should Not Be an Afterthought –

MDM manages information about customers, patients, employees, and other third-party data, which often includes sensitive information such as Social Security numbers and account numbers. Managing this data can be daunting without appropriate data security controls. A cloud MDM strategy must prioritize master data security for both data in motion and at rest. Companies must consider several master data security aspects to ensure robust protection.

3. Be Modular and Take a Phased Approach –

Organizations rarely implement a full end-to-end MDM solution all at once. The best practice is to follow a phased approach, starting with straightforward use cases and progressing to more complex ones. A cloud-based MDM solution should support these phases, allowing organizations to start with small projects that offer quick wins and scale as needed. This flexibility enables the use of the same solution for new business initiatives.

4. Think Hybrid –

Hybrid clouds are popular because they combine the cost benefits of public cloud infrastructure with the customization and privacy of a private cloud. A hybrid MDM strategy allows quick deployment, smooth scaling, and secure data management, making master data easily accessible for real-time analytical applications.

5. Focus on Future Roadmap – 

MDM requirements evolve with changing business demands. Organizations often start by addressing customer data challenges and then move on to complex use cases such as product, supplier, and employee data. For instance, Schlumberger uses MDM to master more than 25 domains. A cloud-based MDM solution should support this continuous evolution.

6. Data Governance and Stewardship –

Effective MDM defines and enforces policies regarding data collection, quality, protection, access, use, and retention. Governance and stewardship are crucial for maximizing business value and minimizing risk. A robust cloud-based MDM solution should include ownership and accountability, consent management, privacy and protection, embedded controls, monitoring and analysis, and audit and reporting.

7. AI and Machine Learning –

AI and machine learning (ML) processes require vast amounts of data to deliver meaningful insights. A modern cloud-based MDM solution should apply AI and ML to automate data stewardship and provide actionable insights. As data volumes grow, leveraging AI and ML techniques becomes essential for efficient data management.

8. Modern Architecture –

To meet modern organizational needs, a cloud-based MDM solution must reside on modern architecture. The solution should be portable, support microservices for continuous updates, and be scalable in terms of data size, sources, and users. This architecture ensures agility and flexibility, enabling organizations to adapt quickly to changing requirements.

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Case Study: The Health Collaborative and IBM – Leveraging Data for Improved Healthcare

The Health Collaborative, in partnership with IBM, implemented IBM InfoSphere Master Data Management (MDM) to enhance the quality and coordination of healthcare. This case study explores how the organization leveraged data during the COVID-19 crisis to improve patient outcomes and streamline healthcare processes.

The Challenge

During the COVID-19 pandemic, the need for accurate and accessible healthcare data became paramount. The Health Collaborative, serving as the coordinator for the Greater Cincinnati Disaster Preparedness Coalition (DPC) and the only Health Information Exchange (HIE) for disaster response in the region, faced the challenge of integrating and managing data for over 9 million individuals across 270 member hospitals and health systems.

The Solution

Working with IBM, The Health Collaborative developed a master patient index (MPI) using IBM InfoSphere MDM. This platform created a single, accurate record for each patient, facilitating better data integration and management. The MPI enabled efficient notification of physicians about patients who tested positive for COVID-19, ensuring timely and accurate information sharing.

Conclusion