Data Governance Best Practices
Five core processes support every data governance program:
- Discovering and inventorying data, including tracking its movement
- Documenting data definitions, policies, standards, processes and ownership, as well as analyzing dependent processes
- Enforcing data governance policies and business rules, and applying data stewardship
- Measuring and monitoring the results, ideally in real time
- Democratizing data use to quickly connect business users to the data assets they need
You also want to ensure that everyone affected by the project is appropriately engaged. Which means that every individual project needs stakeholders in these key roles:
- Driver: An owner dedicated full-time to pushing the project forward.
- Approver: Those who are accountable for key decisions and can provide all necessary resources.
- Contributors: Business and IT subject matter experts who provide necessary context. These include business leaders, process owners and stewards. They can also include IT architects, analysts, and systems experts. Your initiative will impact their upstream and downstream processes.
- Informed: Anyone affected by the project. This group includes data consumers who will benefit from improved data quality and reliability. It will also include people who do not directly benefit, but whose behaviors and processes will have to change.
Learn how to start and continue a successful data governance program
Download your copy of The Data Governance Program Workbook, a step-by-step guide to launching a Data Governance program.
IT and business leaders must work hand in hand to make sure each understands the other's goals. A collaborative approach is key to communicating the value and impact of data governance across your entire business. Establishing a steering committee usually makes it easier to align the wants and needs of different departments. This steering committee can help make strategic decisions about the direction of your data governance program.
Understanding data governance challenges
Establishing an enterprise data governance program makes it easier for employees to align, understand, scale and collaborate.
Align and Understand
Employees can align on appropriate uses of data and drive business outcomes with trusted data. To build greater awareness and understanding of how data is a critical asset, you can also establish and enforce a single set of policies and processes for collecting, storing and using data.
Scale and Collaborate
You need to scale that framework and its core processes to reach everyone. You should also be able to collaborate with everyone, across multiple disciplines. Everyone should be able to take part in the data governance process.
If you don’t know where to start, it can be no small feat to develop and launch a data governance program. It may seem easier not to begin. But failing to govern your data well can lead to consequences. Consequences such as lower productivity when driving new business value. Or risks such as regulatory penalties, brand damage and loss of market share. But when you get data governance right? You speed time to market for new products and services. You gain a better understanding of your consumers, and that helps you improve customer experience. You’re also able to ensure that your analyses are accurate and trust them to make better, faster decisions.
Ensuring Your Data Governance Program is a Success
How do you make sure your data governance program is successful? A good place to start is to help your employees understand how engaging with data governance benefits everyone. Plan to retool your business environment so that everyone — not just data stewards — can access knowledge about data as well as the data itself.
Intelligent Data Governance to Accelerate Your Data-driven Digital Transformation
Executing on data governance
Data governance is not a standalone initiative. Finding data, and then creating a glossary and dictionary to standardize semantics, is only the beginning. Consider it the equivalent of setting up a new department, one that touches every other department. Want your data governance practice to thrive? Then you'll need to establish priorities and determine where to direct its efforts on an ongoing basis. And that means you need to make sure you have the right level of executive sponsorship. As with any other project you hope to scale, it makes sense to start with a project that's small enough to be achievable, but still capable of delivering results. Ensure you have clear alignment with business stakeholders for the project. Set achievable goals and define them clearly to keep the project on track. You’ll want to use both quantitative and qualitative metrics to measure success. Ideally, your project should have demonstrable value, ready-made sponsors, and the potential to scale or expand by creating additional opportunities to extend data governance. You should also have tools that promote agility and flexibility. That way, you can start small and scale quickly, leveraging the capabilities you need at each step of the process.
How to start with just enough data governance
Data Governance Examples and Use Cases
After decades of allowing all of their different divisions to manage their own data, textbook publisher McGraw-Hill Education faced a data quality nightmare. They wanted to combine all of their data for an enterprise-wide business intelligence initiative. To help stakeholders work together, they created a data governance team and deployed Informatica data governance solutions. That led to critical improvements such as:
- Standardizing data quality rules and metrics across the company
- Centralizing a single source of truth
- Fixing data issues before they propagate downstream
- Giving stakeholders the autonomy to make changes within their functions
- Documenting processes to find inefficiencies, clarify goals and assign ownership
Using the right data governance technology solution has helped McGraw-Hill Education consolidate to a single, reliable source of product data. Up next? Their customer data.
AIA Singapore is an insurance and financial services provider established in1931. They wanted to gain deeper market insights and achieve better, more personalized relationships with their customers. To realize that goal, they needed a better understanding of their business and customer data. AIA began by setting up a Data Governance Council. The council developed the data governance framework, policies, processes and standards. They then used Informatica solutions to develop a collaborative business glossary. Scanning and indexing metadata from core systems helped them understand how data was being used. It also allowed them to monitor data quality in real time. AIA Singapore can now follow data end-to-end through the organization. They can track how it is transformed and provide this reliable data to insurance agents and employees. These stakeholders can use these trusted insights to optimize sales, improve decision-making and manage costs.
The biggest data governance challenge is adapting to changing needs and requirements. Today, you may be improving data quality in a single business unit. Tomorrow, you may need to fuel data analytics and govern AI models to provide insights into your customer experience program. Or you may want to improve operational efficiencies to lower costs. You need a technology platform that can scale and evolve to incorporate new data and business applications. You need technology that won’t compromise speed or effectiveness — but will deliver data to those who need it most.
Informatica's platform is cloud-native, modular, interoperable and scalable. Its elastic compute power and storage enables data governance at any volume, so you can match your growing consumption needs. Artificial intelligence allows automated, accelerated data discovery, cataloging and self-service marketplace capabilities. Thanks to metadata management, your team can focus on connecting new systems and extracting more value from your data. Our centralized, extensible data governance console is designed to connect data lineage to business processes. This allows you to document processes and align workflows across your business. Our platform makes it easy for everyone in business and IT to understand their roles in your data governance strategy. And it helps to clarify how their use of data aligns with your company's data governance standards.
Learn more about the critical importance of consistently and collaboratively improving the trustworthiness and quality of data across your organization.
Data governance resources
- The Data Governance Program Workbook: A step-by-step guide to launching a data governance program
- Just Enough Data Governance: Our e-book about taking an efficient path to data governance
- Data Governance vs. Data Management: What’s the difference?
- 4 Steps to Scaling a Data Governance Program
- Reimagine Data Governance Webinar: Lineage, a map for the data explorer
- What is Data Governance?
- How to Use Data Intelligence to Drive Better Business Decisions