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What You'll Learn
Here’s a question for you: Do you think your data is trustworthy and secure enough to facilitate confident business decisions? If you are not sure yet, it’s time you accelerate investments in data governance best practices and strategy. After reading our blog, you will know the answers to the following questions:
- What is data governance?
- Why does data governance matter?
- Who is responsible for data governance?
- What are the best practices for effective data governance?
What is data governance?
Data governance is the end-to-end management of data availability, data usability, data integrity, data security, and data compliance across your entire organization. Simply put, data governance refers to the strategic framework that defines three things – how your data is managed, how your data is protected, and how your data is used within your organization.
It encompasses all the policies, procedures, roles, standards, and metrics that ensure the effective and responsible use of data.
Why is data governance important?
Data governance is important because it makes your data usable, trustworthy, and protected. Here are the top reasons you should consider data governance for your organization.
- Your expenses and business risks are reduced.
- There is more efficiency across teams.
- There is better data trust.
- You are ready for AI and better data compliance.
Get more details in our Enterprise Data Governance Guide.
Who is responsible for data governance?
Effective data governance will require you to facilitate a collaborative structure. Here’s a look at the key roles involved:
- Chief Data Officer (CDO)
CDO will lead the data governance program and align it with your business goals. CDOs are accountable for setting governance strategies and driving enterprise-wide adoption.
- Data Governance Council
This is a cross-functional data governance committee of business leaders, IT, and compliance officers that helps define data governance policies, prioritize governance initiatives, and resolve conflicts if any.
- Data Stewards
Data stewards are the domain experts responsible for maintaining data accuracy and consistency within their specific areas. They implement data governance policies, flag issues, and ensure data governance standards are upheld.
- Data Owners
They are accountable for specific datasets and are responsible for granting data access, reviewing data usage, and ensuring data quality and data compliance.
- Data Consumers
These include data analysts, developers, business users, and AI teams who rely on governed data for their work.
What are the best practices for effective data governance?
Let’s face it! Data governance isn’t about creating policies or installing a modern tool. It’s about building a robust framework – a framework that makes your data work for your business. Here are some of the best data governance best practices that you must follow to ensure your data is trusted, discoverable, and usable at scale.
1. Start with ‘why you need data governance’
The first thing that you need to do when initiating your data governance project is to ask yourself a couple of questions. This is where every strong data governance initiative begins. There’s no point rolling out governance because it’s a trending term. Ask yourself: “What business problem am I solving with data governance?” “Am I struggling with customer data duplication?” “Is there regulatory pressure in my industry?”
Remember, when you identify a clear business driver, you make sure that your governance framework or initiative is relevant. When everyone on your team understands the ‘why,’ data governance becomes a shared goal rather than a checklist.
2. Think of data as a product
When you treat data as a product, you naturally start caring about the user experience. Considering data as a product means each dataset will have its own consumers. They can be internal teams, data analysts, data owners, data engineers, or other business units. And like any product, good data must be reliable. It should be well-documented and continuously improved based on feedback. When you make this shift in mindset, you set up accountability. Product owners become responsible for the usability and quality of their data domains. It encourages teams to deliver “fit-for-purpose” data.
3. Leverage active metadata to make your data more discoverable
Quick question: Can you govern what you can’t find or understand? That’s where metadata comes in. But there’s one thing to note here. You need not rely on static documentation! Forward-thinking organizations use active metadata. This means metadata that updates in real time based on how your data is being used, where it’s flowing, and who’s accessing it. Active metadata powers intelligent data discovery, automated data lineage, anomaly detection, and policy enforcement. When you pair it with a modern data catalog, it helps your teams find the right data faster, understand its context, and avoid duplication or misuse. You can consider active metadata as the backbone of self-service governance.
4. Make sure data quality is a shared responsibility
Don’t think data quality is the sole responsibility of your IT or the data team. It’s everyone’s business. The best governance programs embed data quality into daily workflows. That means:
- You need to set up data quality rules and data quality checks at ingestion.
- You need to create data quality scorecards that are available to technical and business users.
- You should encourage a culture where users can highlight data issues and see them resolved quickly.
Make data quality a collaborative effort.
5. Democratize data ownership. Use federated governance models
Centralized governance might give you control, but it doesn’t scale. As your data ecosystem grows, a federated governance is a safe and good option. The model allows your teams to own their data while still adhering to shared data standards and policies. This approach works particularly well when:
- You have multiple business units or regions operating independently.
- You’re adopting data mesh architecture.
By enabling local data ownership with central oversight, you strike the right balance between autonomy and accountability.
6. Leverage the right data governance tools & technologies
Gone are the times when good governance was manual. Today’s market is full of powerful data governance tools like Informatica Axon, Informatica CDGC, Collibra, and governance-native features within Snowflake and Databricks. These tools can help you:
- Automate data lineage and cataloging
- Classify sensitive data
- Manage data access controls
- Monitor data quality in real time
But! Never choose tools in isolation! Select platforms that align with your tech stack, your data maturity, and your business needs. The right tool should support automation, enable business users, and give you visibility across the data lifecycle. LumenData can help you with technology selection and deployment. With over 273 certifications, LumenData is partners with some of the leading data platforms in the market.
7. Think small first, then scale
Are you thinking about launching a massive, enterprise-grade governance initiative? We do not recommend this. We suggest beginning with a focused use case that delivers quick wins. It could be anything – improving customer data quality or ensuring regulatory compliance in finance. How does the start small approach help? Well, it helps build momentum, gather feedback, and demonstrate tangible ROI. As teams see the value, you can expand the governance program to cover more domains and functions. By proving success early, governance transforms from a checkbox activity to a value-adding discipline embraced across your organization.
Choose LumenData for data governance consulting and implementation services
LumenData approaches data governance in a pragmatic manner. Data governance can seem complex, but we simplify it for you.
At LumenData, we specialize in end-to-end data governance consulting and implementation. We do data maturity assessments, data strategy, data governance tool implementation, data cataloging, and data stewardship setup. We have expertise in leading data platforms like Informatica, Collibra, and Snowflake. We ensure your governance model is technically sound and business-ready.
With LumenData, you can enable data governance at every level. Modernizing your data stack? Preparing for AI readiness? We’re here to help.
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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