Data governance solutions

Everyone’s talking about artificial intelligence (AI). And with the rapid expansion of business opportunities created by these solutions, it’s easy to see why, whether you want to harness its power to:

• Increase internal productivity
• Attract and retain customers with more personalized experiences
• Generate new ideas for competitive advantages
• … and much more

But most organizations are struggling to get their data ready for training models, leading to AI systems that produce skewed outputs and , not to mention the added complexity of expanding AI regulatory scrutiny bringing in even greater risk – and heavy noncompliance fines if you don’t ensure proper data handling.

And AI governance isn’t just about managing the data that feeds your models—it’s about ensuring AI itself is used responsibly, effectively, and in compliance with evolving regulations. How do you monitor AI outputs for accuracy and bias? Can you quickly adapt governance policies to meet new internal and external requirements? Are you tracking who is using the model, how it’s being applied, and whether it aligns with ethical and business guidelines?

The success of your AI initiative relies on having comprehensive and flexible data governance framework to avoid common pitfalls.

A robust data governance solution answers critical questions like:

• Do my AI models meet the most current regulatory requirements?
• Is this dataset appropriate for my model?
• What policies apply to this data? Does this data contain sensitive PII?
• Is the data high quality? Is the data being observed for changes outside of needed parameters?

Adopting the right data governance framework and capabilities ensures the quick success of your AI initiative, while avoiding common challenges and embracing all of the benefits and competitive advantages that come along with it.

Get ready for AI-powered wins by managing your AI data policies and processes with the Precisely Data Integrity Suite Data Governance service confidence. Whether you’re leveraging built-in AI capabilities or bringing your own LLM model through our AI Manager capabilities, Precisely’s Data Governance service ensures your data is trusted, compliant, and ready for AI-driven insights. With automated policy enforcement, model transparency, and workflow accountability, you can mitigate risks, streamline oversight, and maximize the impact of AI across your organization.

Need to harness the full potential of your data assets to keep up in a data-driven world?

Effective data and analytics governance is crucial.

But data governance presents unique challenges, particularly in empowering business users with the tools and understanding necessary to leverage data efficiently and responsibly.

That’s what makes a business-friendly, flexible data governance framework essential. It should enable your business users, in near real-time, to:

• Easily understand metadata for critical data products
• Associate the policies governing their usage
• Know the procedures for gaining access
• Increase AI and automation to boost productivity
• Leverage machine learning for smarter, more efficient governance

This level of transparency ensures data governance while also fostering a culture of data literacy and compliance across your organization, so you can be sure that your data insights are timely and relevant. It’s no surprise, then, that flexible data governance has become a requirement in modern data architectures like data fabric and data mesh that are deployed to increase trust and agility in data and analytics.

An intuitive  data catalog is also vital for users to quickly identify and understand existing data products within your organization – including technical metadata, data quality, and lineage.

Data catalogs provide a clear, up-to-date inventory of data, which helps you prevent redundancy and accelerate the data discovery process. Then, you can move forward with better, more confident decision-making and greater operational efficiency.

With our new personalized views, Precisely’s data catalog delivers a modern, intuitive experience with a card-based interface, making it easier than ever for non-technical and technical users alike to navigate, discover, and manage data assets. It automates metadata collection, applies data profiling rules, and continuously monitors data for anomalies, ensuring your data is accurate, trustworthy, and ready for action. Seamlessly integrating business metadata like ownership, policy management, and impact analysis, the catalog provides context-rich insights that empower users at every level. With scalable architecture, deep connectivity across data ecosystems, and future-ready adaptability, it simplifies governance while supporting evolving data strategies like data fabric and data mesh.

Integrating these elements into a modern governance solution ensures that your data and analytics governance enhances business agility while maintaining compliance.

Empower your users with easy-to-use tools and clear, real-time data insights, so you pave the way for innovative data-driven strategies and solutions that drive business growth and competitive advantage. With a focus on data stewardship, and a flexible metamodel, you can govern data in a way that aligns with your unique business needs. Whether enforcing strict compliance controls, managing operational data, overseeing functional domains, or enabling AI experimentation, our governance framework supports diverse use cases —ensuring agility without sacrificing accountability.

Watch the webinar: Enabling Real Time Data and Analytics: Key Considerations and Best Practices.

A business-friendly approach to data governance is imperative to engage all users and accommodate diverse business use cases spanning analytics, operational improvements, regulatory compliance, AI governance, and risk management. To increase adoption and collaboration, business and technical data users across your organization need to have a common, agreed-upon, and documented understanding of which data is most important, what it’s called, and where it’s used.

Modern data governance solutions jumpstart this alignment with an intuitive and easily understood framework – or metamodel – that mirrors your business model to increase familiarity and facilitate adoption. It’s also important to be able to search with everyday language with semantic tagging to easily find similar and related assets.

Best-in-class data governance solutions provide dynamic visualizations that help users quickly understand the lifecycle of their data and critical relationships across systems and processes. Business-friendly data lineage, impact analysis, and process maps gives users even greater context, improving confidence in data-driven decisions.

Data stewardship is also a critical component of business-friendly governance. Your data governance solution should offer tools that can be managed by the business that empower stewards to document, oversee, and enforce governance policies without requiring deep technical expertise or manual intervention. Features like automated workflows for approvals and policy tracking, consolidated metadata management, and AI-powered recommendations ensure stewards can proactively maintain data integrity, resolve issues efficiently, and enforce compliance at scale.

Automation also contributes to increasing data literacy and delivering solutions that are truly business-friendly. Your data governance solution should be able to quickly crawl, profile, and score complex metadata while providing accelerators to automate metadata ingestion, ensuring your data catalog remains fresh and current.

Learn about the top 4 priorities for building a data governance program that consistently delivers business value to your team.

Data quality and data governance share a symbiotic relationship—both working together to ensure data is accurate, consistent, and reliable for better business outcomes. A key goal of many data governance programs is to increase visibility into data quality so organizations can trust the data driving their decisions.

Governance requires the right data quality tools—not just to clean raw data, but also to identify errors, enforce standards, and monitor data quality over time. Increasingly, machine learning capabilities help optimize data quality by detecting patterns and trends, making it easier to prevent issues before they impact operations.

Your data governance solution should be compatible with industry-leading data quality solutions to surface data quality scores on key assets, ensuring teams have real-time insights into the health of their data. With scalable remediation capabilities, organizations can proactively detect, flag, and resolve quality issues at scale through automated workflows, AI-driven recommendations, and clearly documented processes. This ensures faster resolution of data issues, greater operational efficiency, and stronger data-driven decision-making across the enterprise.

Proving the value of your data governance program should be approached both as an ongoing strategic practice and embedded in your chosen data governance solution. Without metrics of how your governance initiative is impacting your business goals, your program is at risk of losing sponsorship and funding.

To accelerate new governance programs, you’ll want to fortify existing data governance programs through proven ROI. To reinforce confidence in the value of governance initiatives, you must identify, connect, and measure data assets linked with:

• Business Goals, objectives, KPI’s and metrics
• Critical business processes and operational performance
• Transformational, compliance or analytical initiatives

A value-based approach highlights that data governance is not just another ‘have to do’, but a critical strategic program with measurable outcomes.  And while the right products are required, the people and the processes that support them must be in alignment.  If you are asking yourself questions like ‘how do I get started’ or ‘how do I measure the ROI of my governance initiative’ Precisely can help.  With our unique in-house data consulting team, leverage our proven methodology to create a sustainable and repeatable strategy for data governance success.

Check out this customer story that explores how Keurig Green Mountain implemented an enterprise data governance solution to realize their strategic vision and build a scalable framework for long-term success.

Data governance plays a pivotal role in the successful implementation of data mesh and data fabric architectures, which are designed to manage data across diverse environments effectively.

Both data mesh and data fabric aim to enhance data accessibility, quality, and integration, but they approach data governance differently:

• Data mesh decentralizes data governance, allowing domain-specific teams to manage their data autonomously, fostering agility and innovation.
• Data fabric centralizes data governance, ensuring data is harmoniously integrated and consistently governed across the entire organization.

With data mesh, effective data governance is critical. It empowers your domain owners to maintain their data independently while adhering to overarching organizational policies, and ensures that each domain’s data is accurate, compliant, and securely accessible. With this structure, you can:

• Gain stronger trust in and reliance on the data products generated
• Power rapid, localized decision-making
• Increase responsiveness to specific departmental needs – without creating risk around privacy and security of data

With data fabric, data governance provides the framework to ensure that data across your organization is standardized, compliant, and properly managed, regardless of where it resides. This centralized approach to data governance supports:

• A unified view of accurate and timely data
• Comprehensive risk and compliance
• Better decision-making through greater data literacy

Regardless of which architecture is right for you, robust data governance is essential for mitigating risks, ensuring compliance with regulations, and maintaining data quality.

It fosters a culture of data literacy and trust by establishing clear protocols for data usage, privacy, and security. By enhancing visibility and control over your data, governance frameworks within data mesh and data fabric architectures help you make more informed, confident, and effective data-driven decisions across your business.

Prepare for modern data management architectures today with the Precisely Data Integrity Suite.