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MDM Master Data Management

Master Data Management (MDM) is a method for defining and managing the critical data of an organization (also known as master data). Master data covers core business entities such as customers, products, employees, suppliers, and these often reside in siloed data repositories even within the same organization. MDM seeks to ensure this data is consistently defined and interconnected.

Components of MDM

  1. Data Collection: Gathering data from various sources.
  2. Data Transformation: Converting data into a common format.
  3. Error Detection & Correction: Identifying and correcting data errors.
  4. Data Governance: Implementing management policies, procedures, and governance to ensure data quality.
  5. Data Maintenance/Quality Assurance: Ongoing processes to keep data up to date and of high quality.

Key Objectives

  1. Data Quality & Business Process Management Efforts: Ensures that data is accurate, consistent, actionable, and pertinent.
  2. Business Intelligence: Drives analytics and data mining, empowering business decisions.
  3. Compliance: Aids in compliance with various laws and regulations related to data.

Types of Master Data

A typical entreprise / organisation will have the following data that are relevant to MDM:

  1. Customer Data: Information about customers and prospects.
  2. Product Data: Information about products that a company makes or sells.
  3. Employee Data: Information about employees in an organization.
  4. Supplier Data: Information about suppliers and supply chain logistics.
  5. Asset Data: Information about physical and virtual assets and their attributes.

MDM Processes

  1. Data Collection: Aggregating data from disparate sources.
  2. Data Transformation: Standardizing and enriching data.
  3. Data Governance: Applying rules, policies, and governance.
  4. Data Maintenance: Ongoing quality assurance processes to keep data accurate, timely, and relevant.

Benefits of MDM

  1. Enhanced Compliance: Better data handling and records for compliance with legal and business policies.
  2. Improved Efficiency: Reduces redundancy and eliminates the expense of having to reconcile data inconsistencies.
  3. Better Decision-making: Provides a ‘single version of the truth,’ making data more reliable.
  4. Customer Satisfaction: Improved data quality provides more accurate insights into customer behavior, enabling better service.

Challenges in Implementing MDM

  1. Organizational Silos: Data residing in disparate parts of the organization, in different formats, and maintained by different units.
  2. Data Quality: Ensuring data is clean, accurate, and up-to-date.
  3. Data Governance: Establishing the roles, responsibilities, and procedures for data quality, consistency, and usage.
  4. Technology & Tools: Implementing the right MDM solutions that fit the organization’s needs and scale.

MDM and Open Source

Open-source solutions for MDM enable organizations to implement these processes without the burden of licensing fees and with greater flexibility to customize the system to their specific needs.


Page last modified: 2023-10-13 12:07:36