Four Data Management Trends Reshaping Business in 2025

A CTO’s Perspective on What’s Next

As I step into my new role as CTO at Actian, I’m struck by the profound changes affecting the data management landscape. These changes are not only driven by the deployment of AI, but by organizations wrestling with more data in more places than ever before. While these shifts create exciting opportunities, they also bring new challenges that will reshape how we think about data management in 2025. Here are four key trends I see emerging:

1. The End of One-Size-Fits-All Data Governance

Remember when all roads led to the data warehouse and a single authority managed data governance or to data lakes containing big swaths of ungoverned data? Those days are ending. In 2025, we’re embracing a decentralized reality where data gravity dictates where data lives. Because of this new reality, organizations need to adapt their governance approach to manage data wherever it lives.

Federated governance combines centralized standards with domain-specific flexibility. Think of it like this: your marketing team understands marketing data best, and your finance team knows their numbers inside and out. Why not let them manage their own data domains while maintaining company-wide standards? This approach means better, more relevant governance without sacrificing compliance, quality or security.

Domain-oriented data owners are active participants in the governance program by communicating company policies and other regulations assigned to their data through a data catalog. The data catalog makes data discoverable and accessible, enabling data sharing and collaboration across the organization. By granting widespread access to trusted data, businesses can enable employees at all levels to make informed decisions.

2. Welcome to the Data Ecosystem Era

Here’s a truth that might sound familiar: your organization’s valuable data isn’t just in databases and warehouses. It’s in PowerPoint presentations, email exchanges, PDF documents, Excel sheets, and countless other formats scattered across shared drives and cloud storage. In 2025, successful organizations will stop ignoring these diverse data sources and instead embrace them as part of their complete data ecosystem.

The shift to interconnected data systems and diverse data tools requires a focus on interoperability. Data lineage also becomes important for a complete view of the data’s life cycle – from its collection to its use, storage, and preservation over time.

But this evolution isn’t just about technology – it’s about people too. With skilled data professionals in short supply, organizations need to foster data literacy across all teams, standardize a glossary of data terms, and encourage continuous learning to keep pace with technological change.

3. The Rise of the Enterprise Data Marketplace

Imagine if finding and using data in your organization was as easy as shopping online. That’s the promise of the enterprise data marketplace. In 2025, we’ll see more organizations treating their data as products that can be easily discovered, understood, rated, and used internally.

This marketplace approach isn’t just convenient – it’s transformative. Teams can publish their high-value data assets (from datasets to dashboards to AI models) as data products, which preserve critical context about quality, origin, and usage rules. Other teams can then find and use this data through a familiar, e-commerce-like experience.

4. Data Quality: The Foundation for AI Success

As AI becomes more central to business operations, one truth remains clear: even the most sophisticated AI models are only as good as the data that powers them. In 2025, data quality will become even more critical, but we need to think about it in two ways.

First, there’s the objective side of the data – factors like accuracy, completeness, and timeliness. Equally important is the subjective side of the data – trust and purpose. For example, a partially completed customer profile might be perfectly fine for a marketing campaign but useless to the finance team if the verifiable billing address is missing. Understanding these context-dependent quality requirements will be crucial to preparing data for successful AI implementations.

Looking Ahead

These trends point to a future where data management becomes both more sophisticated and more intuitive. Organizations that adapt to these changes – embracing decentralized governance, building comprehensive data ecosystems, enabling marketplace-style data sharing, and maintaining high data quality – will be best positioned to thrive in 2025 and beyond. As a result, they will have deeper intelligence into their data, being able to leverage it for strategic decision-making and to deliver business value.

The good news? The technology to support these shifts is already emerging. At Actian, we’re focused on helping organizations navigate this transition, making it easier than ever to unlock the full potential of their data while maintaining security and governance. The future of data management isn’t about building higher walls – it’s about building better bridges.

About Emma McGrattan

As Chief Technology Officer at Actian, Emma McGrattan leads the company’s technology strategy, innovation, and product development in support of Actian’s mission to simplify how companies connect, manage, govern, and analyze data to transform businesses. Since joining the company three decades ago, Emma has played a pivotal role in the evolution and advancement of its analytics, data integration, and data management solutions, including the Actian Data Platform. Emma holds a degree in Electronic Engineering from Dublin City University in Ireland.