The proliferation of data sources and distributed systems has turned data governance into an expensive firefighting operation. Companies have invested heavily in data stewards, governance platforms, and comprehensive policies – yet we are still answering the same question repeatedly: “Can we trust this data?”

Chief Data Officers find themselves caught in a reactive cycle that feels impossible to break. Quality issues surface in executive dashboards at the worst possible moments. Business users approach insights with skepticism rather than confidence. Data teams spend the majority of their time preparing data rather than generating insights.

Meanwhile, data distributed across multiple systems and business units makes enforcing consistent quality and governance standards feel impossible.

The hidden costs of this reactive cycle run deep. With unreliable data, organizations risk flawed or failed AI implementations, taking too long for business decisions, low to no ROI, and increased regulatory risk. To reverse the cycle, progressive CDOs are moving from reactive to proactive governance through data contracts that guarantee consistency and quality from the outset.

The problem with traditional data governance

Traditional data governance operates like quality control in the early days of manufacturing – build the product first and then check if it meets standards. This reactive culture is focused on firefighting issues as they arise rather than preventing them from the outset. As a result, data quality problems are discovered only after they reach critical business systems and dashboards. In turn, each incident diminishes user confidence.

Treating data as a product defined and documented via clear data contracts creates a framework for proactive governance and reliable, consistent data usage. These data contracts include comprehensive documentation, quality metrics, and usage guidelines that transform static documentation into active quality controls.

Instead of retrofitting quality after the data product is created, the data contract defines clear expectations, enforces compliance automatically, flags issues in real time, and builds trust at the source.

Transforming to proactive data governance requires three strategic moves: creating data contracts first, automating compliance with embedded governance, and evolving teams into data and AI literate innovation enablers.

Strategic move #1: Create data contracts first using shift left principles

The first strategic shift involves shifting governance left in data pipelines – moving quality controls earlier in the development process. This “governance by design” approach builds governance into the DNA of every data interaction instead of bolting it on later.

The most successful implementations integrate data contracts directly within continuous integration and continuous deployment (CI/CD) pipelines. That way, when developers attempt to merge code changes that violate the contract, the system automatically blocks those changes. This proactive prevention transforms data teams from reactive firefighters into proactive engineers.

Strategic move #2: Automate compliance with governance embedded at the source

By creating the data-contract-first – before building the data product – compliance transforms from a manual, reactive process into an automated capability. With governance policies embedded directly into data contracts, compliance becomes self-enforcing rather than dependent on human oversight. As a result, the governance team shifts from being a bottleneck to being an enabler.

This approach becomes especially powerful in a decentralized environment where different business units own their domain data and independently create data products. Data contracts provide universal federated governance standards that enable secure, efficient enterprise-wide data sharing. Privacy controls, retention policies, and access permissions are also defined within each contract, which travels with the data product as it moves through pipelines and systems.

With automation, compliance becomes continuous, not a scramble when auditors arrive. When regulations change, policy updates flow automatically to all relevant data products rather than requiring manual updates across systems.

This transformation from reactive firefighting to proactive governance reduces both operational costs and compliance burdens so CDOs can focus on strategic initiatives that drive business value.

Strategic move #3: Evolve your team from firefighters to innovation enablers

The final shift is cultural – shifting how people engage with data from reactive firefighting to proactive value creation. Data stewards evolve from compliance police to marketplace curators who certify high-value data products. Data engineers shift their focus from fixing quality problems to preventing them through contract automation. Business users transform from passive data requesters to active data product partners who collaborate on defining contracts and requirements.

This transformation requires careful change management with regular leadership communication and investment in upskilling. 

From reactive metrics to strategic impact indicators

CDOs implementing data contracts first can track various metrics to demonstrate governance transformation. Rather than measuring only reactive indicators like incident resolution times, teams can measure proactive metrics like data product adoption rates, decision velocity improvements, and analytics team productivity gains.

The long-term value of getting governance right

While most organizations continue throwing resources at reactive governance approaches, those implementing data contract first strategies are building flexible data ecosystems that scale quality and governance automatically. While others debate data definitions, these organizations are creating AI-ready data and making confident decisions based on trusted data products with built-in guarantees.

You don’t need a complete overhaul to begin. Start small: pick a high-friction data asset, draft a contract, and implement one automated quality check. That early win typically justifies broader adoption. This initial success opens the door to broader transformation. 

Organizations mastering data contract first strategies establish sustainable competitive advantages in data-driven decision-making, creating cultures where data trust enables rather than constrains innovation. The question isn’t whether to evolve your governance strategy – it’s whether you’ll lead this transformation or be forced to follow.

About the Author:

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, McGrattan has played a pivotal role in the evolution and advancement of its analytics, data integration, and data management solutions, including the Actian Data Platform.

A prominent figure in the database industry, McGrattan is known for her expertise in data architecture, query optimization, and cloud transformation. Her leadership and contributions to these areas are widely recognized, making her a respected voice at technology events.

Passionate about creating a sustainable, inclusive future for technology, McGrattan is a celebrated advocate for women in tech and an active mentor dedicated to fostering inclusive cultures within the industry.