Aviation runs on complex, fast-moving data. Every decision requires high levels of precision, and the interconnected nature of the industry means that data quality impacts operational, financial, and safety outcomes.
To address how organizations can manage this critical asset, Sarah Davis, VP for Data at Cirium, and Candice Parfitt, Head of Data Governance at Cirium, recently presented the Data Governance 101: Aviation Foundations webinar. They shared how Cirium structures its internal data governance and why establishing a solid data framework is essential for modern aviation operations.
Key highlights
- Trust is paramount: Data governance involves aligning the right people, processes, and technology to build reliable, accurate datasets.
- AI requires a solid foundation: Artificial intelligence magnifies data issues. Effective AI governance starts with trustworthy underlying data.
- Start small: Organizations should evaluate their maturity and tackle governance initiatives in small increments to provide immediate value.
- Human oversight remains necessary: While AI can augment governance by detecting inconsistencies, human review is crucial for accountability and accuracy.
Defining governance for aviation
Aviation data must meet the same rigorous standards as the industry itself regarding reliability and safety. Poorly governed data creates significant exposure. Data governance is not about adding layers of bureaucracy; rather, it is a strategic necessity that defines how good data needs to be for specific use cases.
Effective governance ensures that data management becomes an embedded practice rather than an afterthought. Organizations need to consider governance at the point of data inception. By implementing data literacy programs, companies can help their teams understand the connections between data quality, ethics, and responsible data use.
The cost of inaction
When data governance is absent, the first symptoms are usually confusion and a lack of trust in the numbers. Teams start working in silos, relying on tribal knowledge instead of a single source of truth.
Without clear data ownership, issues bounce between departments. This creates operational friction and delays time-sensitive decisions. Over time, this lack of clarity prevents organizations from fully leveraging their data assets and makes it nearly impossible to scale advanced analytics or AI capabilities confidently.
Real-world cases at Cirium
Cirium applies these governance principles internally to maintain its data credibility. One key initiative is the introduction of Data Product Managers and Data Governance Councils. These roles provide strategic oversight and embed data governance throughout the organization. Data Product Managers build relationships across teams, foster trust, and explain the concrete value of data sharing.
Even simple issues require governance. For instance, industry acronyms can carry different meanings depending on the department. Establishing agreed-upon definitions eliminates misunderstandings and aligns cross-functional teams. By partnering closely with product teams, Cirium identifies new use cases and ensures its data processes remain robust and relevant.
The role of technology
Technology operationalizes governance strategies. Cirium utilizes Collibra as a central platform to manage data governance at the appropriate level. A major focus is data observability—monitoring data quality continuously from the moment of ingestion all the way to product surfacing.
For operational aviation data, such as flight times, there is rarely a single ground truth. Governance technologies help define authoritative sources for specific purposes while documenting differences in timing, scope, and context. Furthermore, while AI can suggest classifications and detect anomalies, it serves to augment rather than replace human oversight. AI systems will produce confident answers even if the input data is wrong, making a governed data foundation the prerequisite for any AI initiative.
Building a mature data governance framework takes time, but the value of accurate, trustworthy data is clear. Tackling governance in thin slices allows organizations to build momentum and establish a culture of data literacy. By focusing on clear purposes and guidelines, the aviation industry can continue to improve through secure, reliable data sharing.
To explore these strategies deeper and evaluate your own organization’s governance maturity, watch the full webinar recording on demand: Data Governance 101: Aviation Foundations.
