Managing information well is vital to today’s data-driven businesses. As businesses deal with more complex data, two important areas have emerged: data governance and Master Data Management (MDM). Understanding how these two work together is crucial for getting the most out of your data.
Simply put, MDM is a comprehensive method of defining and managing an organization’s critical data to provide a single point of reference. Data governance is the overall management of the availability, usability, integrity, and security of data used in an enterprise.
In this blog, we’ll explore these concepts in more detail, examining how they differ and team up to create a robust data management system. Gartner reports that over half of organizations have already established a data governance framework, and nearly a third are planning to do so. This shows that more and more businesses see data governance and data management as vital.
The Difference Between Data Governance and MDM
While data governance and MDM both play significant roles in managing your business data, they have fundamental differences. Think of data governance as the big picture – it’s about the rules, processes, and standards for managing all your data. Conversely, MDM focuses on creating an accurate view of your core business information, like customer details, product info, and location data.
Data governance covers all data types in your organization, but MDM mainly deals with master data. Data governance sets up roles and responsibilities for data management across the whole business, while MDM involves specific technical processes and tools for bringing data together and keeping it in sync.
When it comes to setting standards, data governance creates policies for data quality, security, and following rules across the board. MDM puts these standards into action, but just for master data. Good data governance results in better overall data management, while MDM gives you a “single source of truth” for your critical business data.
There’s also a difference in who leads these efforts. Business stakeholders usually lead data governance with IT support, but MDM often needs more hands-on involvement from IT for setup and maintenance. Data governance tackles broader issues like helping people understand data better, while MDM focuses on technical challenges like data modeling and connecting systems.
How Better Data Governance Supports MDM
Good data governance and data management work hand in hand to create a strong data ecosystem. Here’s how data governance helps MDM:
- It sets the ground rules: Data governance provides the essential policies and standards that guide MDM, ensuring it aligns with your business goals and follows regulations.
- It clarifies who’s in charge: By setting up clear data ownership roles, data governance helps MDM work better by involving the right people in decisions about master data.
- It sets quality standards: Data governance policies on data quality directly shape MDM processes, leading to more consistent and accurate master data across your organization.
- It helps protect data: Data governance classifies and labels sensitive information, helping MDM systems handle and protect important master data properly and keeping you compliant with data protection rules.
- It creates a shared language: Data governance creates a standard business glossary and metadata repository, helping everyone understand master data entities and attributes in the same way.
- It breaks down silos: The teamwork fostered by data governance helps different departments work together on MDM projects.
- It helps solve problems: Data governance sets up processes for fixing data issues and managing changes, which supports ongoing MDM efforts with clear steps for handling master data conflicts and updates.
- It builds a data culture: By promoting data literacy and a data-driven culture, data governance increases buy-in for MDM initiatives, leading to better use of master data systems.
- It helps with compliance: The audit and compliance mechanisms set up through data governance support MDM by providing ways to monitor and report on master data quality and usage.
Seven Tips for Improving Data Governance to Enhance MDM
To get the most out of data governance and MDM working together, try these strategies:
- Create a mixed team: Set up a data governance committee with people from strategic business units and IT. This committee will ensure MDM initiatives align with your overall business goals and data governance policies.
- Build a comprehensive data catalog: Create a detailed catalog of your master data entities, their attributes, and their relationships. This makes it easier for everyone across your organization to find and understand master data.
- Set clear quality goals: Develop clear data quality standards and metrics for master data. Set up automated monitoring and reporting processes to ensure you meet these standards.
- Create a shared dictionary: Create and maintain a comprehensive business glossary that defines master data terms and concepts. This will promote a shared understanding of master data across different departments and systems.
- Track data journeys: Implement data lineage tracking for master data. This boosts transparency and trust in the MDM process by letting stakeholders easily trace where master data comes from and how it changes.
- Manage changes carefully: Set up a formal change management process for master data. This ensures that any updates or changes to master data are properly reviewed, approved, and documented in line with data governance policies.
- Train and communicate: Develop a training and communication plan to teach stakeholders about the importance of data governance and MDM. This helps create a culture of data stewardship throughout your organization.
Prospective Agility
Data governance and MDM are allies in getting the most value from your organization’s data. Good data governance lays the groundwork for successful MDM by ensuring clear policies, standards, and accountability for data management.
When you invest in both data governance and MDM, you’re better placed to create a single, trusted view of your critical business data. This creates better decision-making and more efficient operations.
Continually improving data governance and data management practices will be vital in adapting to changing business needs and new technologies, ultimately leading to more agile and data-driven operations.