What You Need to Know About Master Data Management

What You Need to Know About Master Data Management

Enhance data quality, reduce costs and improve business efficiency with Master Data Management.

Master data management (MDM) can help organizations enhance their data quality and governance while reducing costs and improving business efficiency. By centralizing and standardizing an organization's core data, MDM solutions provide a single source of truth for everyone to use. This ensures that decisions are made based on accurate, up-to-date information and that critical enterprise data is consistently used throughout the organization.

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What is Master Data Management (MDM)?
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What is Master Data?

Master data is the core information that defines an organization and its business processes. It includes key data assets essential to the business’s analytics and operation like:

  • Customer data
  • Product data
  • Financial data
  • Supplier data
  • Employee data
  • Site/location data

What is Reference Data?

A related type of data, reference data, is often described as the master of master data. It is a non-volatile, stable and widely-used data that categorizes master data and correlates it with external standards.

What is Master Data Management?

Master Data Management (MDM) is the process of managing master data to maintain consistent, accessible information throughout the organization. It ensures that an organization’s critical data assets are consistently managed and aligned with business objectives

It includes identifying, cleaning, standardizing and consolidating data from multiple disparate sources into a single source of the truth and then sharing them via integration techniques across multiple IT systems. This means that all stakeholders within the organization have access to accurate, up-to-date and consistent information.

Any industry that relies on core data to make decisions can benefit from MDM. This includes:

  • Financial Services
  • Insurance
  • Life Science
  • Healthcare
  • Retail
  • High Tech
  • Travel and Hospitality
  • Consumer Packaged Goods (CPG)
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Core Components & Disciplines of MDM

A solid MDM foundation is built on six key concepts:

  • Governance: Ensure that data is accurate, consistent and compliant with organizational standards and policies.
  • Analytics: Provide feedback on the performance of MDM processes and allow for continuous improvement.
  • Organization: Assign roles and responsibilities for data management and stewardship among business, IT and external users.
  • Policy: Define the policies and procedures that govern how data is accessed, used and protected.
  • Process: Set clear guidelines for processes and steps to manage data at every stage.
  • Technology: Use the right tools to support MDM processes such as data warehouses, data quality management tools, and ETL systems.
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MDM Roles & Responsibilities

MDM Roles & Responsibilities

The responsibility for overseeing MDM typically falls to the Chief Data Officer (CDO), Chief Information Officer (CIO), or the Head of Data Governance in most organizations.

Data is a strategic value driver. The CDO or CIO is responsible for making the best use of the data capital to drive business outcomes.

These executives ensure that the organization's data is up-to-date, accurate, consistent, and compliant with regulations. They also help to install, configure and maintain the company’s MDM solution.

Their team typically includes:

  • Solution owners who own relationships with software vendors and manage technical resources.
  • Project managers who manage day-to-day activities and oversee projects.
  • MDM admins who configure the MDM platform end-to-end, from data modeling to user experience.
  • Information architects who work with business and IT users to design data models and processes.
  • Integration developers who connect data management solutions with other applications.
  • System administrators who manage infrastructure and servers for the MDM.

The Head of Data Governance leads the Data Stewardship team, which is responsible for defining and enforcing an organization's data governance solutions and policies.

Their team typically includes:

  • Business stakeholders from different business functions (marketing, finance and HR) who control and make decisions about data governance.
  • Business analysts who draft policies, standards and processes for data governance.
MDM Workflow: How to Get Started

MDM Workflow: How to Get Started

The key components of an MDM workflow include steps for data quality management, data governance and data stewardship.

  • Step 1: Identify sources of master data, object structure and attributes.
  • Step 2: Define standardization and any custom processing logic.
  • Step 3: Create a database for reference data.
  • Step 4: Define governance and security framework.
  • Step 5: Generate profiling, cleaning and loading tools.
  • Step 6: Extract data from different systems.
  • Step 7: Analyze and clean data.
  • Step 8: Load matched data to master database.
  • Step 9: Build and deploy the MDM project.
  • Step 10: Define connectivity to external systems using business processes and web services.
  • Step 11: Create necessary presentation layers.
Benefits of Master Data Management

Benefits of Master Data Management

MDM can help to overcome many of the problems associated with manual data entry such as errors, duplicates and incomplete data. Additionally, it can automate tasks such as data cleaning and quality checks. By providing a single view of the truth, MDM improves decision-making and reduces errors and inconsistencies.

Improve decision-making

By providing a single view of the truth, MDM can help to improve decision-making within an organization. This is because decisions can be made based on accurate, up-to-date, and consistent information, which enables teams to standardize their data and make changes without impacting customer experience.

Improve data governance

MDM can help to improve an organization's data governance by providing a single view of the truth for operations and analytics. This makes it easier to track where data comes from, who is responsible for it and how it is being used.

Increase revenue and drive growth

By providing detailed information about each customer’s needs, MDM can help improve omnichannel engagement and improve customer experience. It also provides an understanding of each customer’s needs by providing a view of their journey from start to finish, creating opportunities for hyper-targeted personalization, upselling and cross-selling.

Improve efficiency

MDM can improve the efficiency of an organization's data management processes by automating many tasks associated with managing data and workflow. It also helps to cut down response time with automatic indexing and improved results.

Minimize Risk & Compliance

MDM can help identify potential problems involving fraud and take steps to mitigate them before they cause any damage. By adjusting to new privacy regulations, it simplifies compliance and reduces security risk.

Improve data quality

MDM improves overall data quality by centralizing and standardizing data, fixing data silos and reducing errors and inconsistencies. Features like “Match and Merge” and “Match Before Create As a Service” that reduce duplicate records and prefill leads with as much accurate information as possible.

Improve Data Governance

MDM can help to reduce the cost of storing and managing data because data only needs to be entered once. Additionally, its compliance tools reduce costs associated with following regulations.

Cloud architecture

Modern cloud MDM can meet the needs of thousands of employees and systems at peak times. It supports real-time operational needs by using an API approach to power systems that support digital and human interactions and improve scalability.

Analytical vs Operational MDM

Analytical vs Operational MDM

Analytical MDM is focused on providing clean, coordinated data for reporting and decision-support systems like machine learning-based analytics.

Operational MDM is focused on providing clean, trusted data to support business processes in real time.

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Analytical MDM

Analytical MDM systems clean and organize data for reporting and business intelligence. They collect it from a central hub and convert it into a format suitable for downstream applications.

An analytical MDM system, in its most basic form, generates master records and IDs that link to analytics, reporting, or data science and business intelligence tools. An analytical MDM system can also communicate changes and insights back to data sources or master profiles.

Operational MDM

Operational MDM is focused on validating data to inform business processes in real-time. This type of MDM requires a much higher level of reliability, performance and accessibility than analytical MDM.

The Reltio platform is commonly used to create a single source of truth data for operational systems like CRM, ERP and procurement. Reltio averages less than 300 milliseconds to complete processes and make data available to operational systems.

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MDM Implementation Styles

MDM Implementation Styles

There are four MDM implementation styles: Consolidation, Registry, Centralized, and Co-existence. The style that best suits your needs depends on the domains you want to involve in your MDM system.


The consolidation approach to MDM involves copying data from source applications into a central hub, where it is matched and merged. The hub creates golden records, which it makes available for distribution to downstream applications or direct consumption by business users and data stewards.

This approach provides added capability in the form of stewardship, which gives data stewards the ability to make data entries, deal with duplicates, and manage rejects. This is a great way to take centrally stored master data and use it for analysis and reporting.



The registry style of MDM is focused on identifying duplicates within data sets pulled from multiple source systems. The system cleans and standardizes the data, attaching a unique identifier to duplicate records. The MDM hub stores an index of this source data, keeping track of cross-references between matching source data.

Registry-style MDM is cost effective and doesn’t require much intrusion into source systems. However, it has higher latency and more limited capabilities than other MDM styles.



The centralized, or transactional, MDM style guarantees the highest-quality data, but it’s also the most intrusive and time-intensive. In this type of system, all systems must constantly connect to the data hub for any updates to their master data, which can disrupt existing business and technical processes.



The coexistence style of MDM is the gold standard for large-scale data distribution models. It creates a consolidated data hub that then feeds updated records back to sources. This provides real-time updates in both the master data and the source systems.

The most significant benefit of this style is that it allows data creation on multiple systems. However, it is complicated to deploy and keep secure, and it requires constant data cleaning.

Master Data Management Best Practices for Business Success

Master Data Management Best Practices
for Business Success

Traditional master data management best practices have largely centered around preserving data quality and data governance. However, modern practices power business transformation and the customer experiences of the future, which include:

  • Always include as much master data as possible for holistic insights and better business outcomes.
  • Make data governance a priority to ensure accuracy and prevent redundancy.
  • Continually update data for privacy management and security.
  • Set clear paths to goals and convey unanticipated growth sectors.
  • Remove dependency on IT for data.
  • Build your MDM to drive business goals.
  • Organize master data for simplicity and scalability.
  • Make master data your data foundation.
Common Use Cases for Master Data Management

Common Use Cases for Master Data Management

MDMs can be used in many different ways.
Some of the most common use cases include:

Responsive data management: Overcome and constraints posed by rigid legacy data systems. MDM systems are agile and scalable, and can help businesses pivot fast with a responsive data strategy.

Efficient and consistent privacy and consent: Master Data Management solutions aggregate, refine, reconcile and relate data from hundreds of sources into a consolidated view. This makes it quick and easy to comply with customers’ preference changes.

Hyper-personalization at scale: MDM systems create a tailored view of each customer interaction to discover and unlock the value of relationships with minimal manual effort. Connected customer data powers hyper-personalized customer interactions, resulting in true customer centricity.

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Fast Track Your Master Data Management Learning

Fast Track Your Master Data Management Learning

Develop your skills and expertise in master data management by taking our on-demand learning. Our learning platform, Reltio Academy, offers a wide variety of engaging materials in contemporary learning formats to help you achieve mastery.

How MDM Solutions Have Helped Others

How MDM Solutions Have Helped Others

Learn how Reltio’s MDM solutions have helped organizations improve data quality, efficiency and decision-making through customer data integration and product information management.

Empire Life
Fulton Bank

Empire Life improved customer experience, increased data pipeline quality and IT team productivity, and gained easier and broader access to trusted data with Reltio’s multi-domain MDM system.

"We were attracted to a true cloud-native, fully-managed SaaS solution to lower our infrastructure costs and increase our agility to deliver business value"

Sandro Palleschi, Manager of Enterprise Data Services, Empire Life

Danske Commodities overcame the challenges of a siloed view and an over-reliance on legacy IT systems that didn’t allow teams to innovate. They used real-time data and Reltio’s cloud-native Connected Customer 360 platform to make business more agile, reduce business costs, build momentum and establish top-management buy-in for key data initiatives.

Fulton Bank improved customer experience and operational efficiency, streamlined customer experience and reduced risk with Reltio’s cloud-native Connected Customer 360 platform, resulting in customer growth.

"Providing a connected experience for our customers is paramount. Our goal is to leverage customer intelligence across the organization – from the customer-facing team to digital channels to back office processes – in order to deliver a unified and streamlined customer experience. We had to think beyond traditional master data management to understand customers' transactions and interactions. By implementing Reltio's cloud-native Connected Customer 360 platform, we are looking to drive delightful customer experiences, resulting in customer growth, operational efficiency, and reduced risk." 

Gotham Pasupuleti, Vice President of Customer Data Delivery, Fulton Bank, N.A.
Why You Need a Cloud-Based Master Data Management Platform

Why You Need a Cloud-Based Master Data Management Platform

Cloud-based MDM provides numerous benefits including increased efficiency, agility, and cost savings. Additionally, a cloud-based MDM platform enables organizations to quickly and effectively deliver analytics and operational data to drive superior business outcomes.

Fast time to value:

Cloud-native MDM can be deployed quickly and easily, without the need for complex on-premises infrastructure. This means that you can start using cloud-native MDM sooner and realize benefits more quickly.

Latest technology and better integration:

Organizations can take advantage of the latest technology with zero downtime and zero-effort upgrades that cloud-native MDM offers. It can also be deployed on all major cloud platforms including Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), providing organizations the flexibility and scalability they need to manage their master data more effectively.

Automated backup and disaster recovery:

Cloud-based MDM solutions offer built-in redundancy and disaster recovery capabilities, ensuring that business data is always available when needed.

Remote access:

With a cloud-based MDM solution, businesses can give authorized users access to data from anywhere in the world, at any time.

Agility and Low TCO:

Cloud-native MDM is highly scalable and flexible, making it easy to adapt to changing business needs. This allows you to respond quickly to new opportunities and challenges. It is also more cost-effective than traditional on-premises solutions, due to the lower costs of infrastructure and maintenance.

Faster implementation and scalability:

Cloud-based MDM solutions provide operational agility by allowing seamless data integration into an existing setup and eliminating the need for on-premise server installations. With the ability to scale storage and processing capabilities and software licensing limits, cloud-based MDM is perfect for businesses that need to change their IT infrastructure quickly and easily.

Enhanced security and compliance:

Cloud-based MDM solutions offer zero-effort security and access permissions, 24/7 monitoring and threat protection, data encryption and compliance support, making them ideal for businesses in heavily regulated industries.

Learn How Reltio Enables Modern Master Data Management

Learn How Reltio Enables
Modern Master Data Management

See how the Reltio Connected Data Platform can give you the speed and flexibility you need to accelerate the value of your data and maximize its impact every day.