Enterprise Information/Data Management

For the operations CNA examines for our clients, data is a foundational component. As data resources tend to have evolved in an ad hoc, decentralized manner, clarity of origin and governance of data are not always present. We look at such questions as:

  • Data origination: Where did it come from (original source or intermediary) and how was it generated (methodology, assumptions, context, etc.)?
  • Data quality: Is the data complete and consistent?
  • Data accuracy: Is the data accurate and representative of reality?
  • Data formats, models, and definitions: Are the data elements represented and documented in a standardized manner?
  • Data governance: What are the organization’s processes for managing its data?

Equally important is an analysis of our client’s systems, which are often producers or consumers of data. In analyzing these systems, we often look at such questions as:

  • What systems are involved?
  • What data do the systems provide, manage, or consume and how do they manipulate the data?
  • Are there multiple systems? If so, what is their relationship: are they compatible, are they redundant, or do they serve different functions?
  • If they process data, what is the value added?
  • Do the current systems meet the needs for the organization’s concept of operations?

CNA takes these questions to support a tailored approach for developing acquisition plans, evaluating technologies and alternatives, and informing solution design and development phases for our client.

Data Management at the Federal Aviation Administration (FAA)

CNA analysts have experience across the full data and information life cycle at the FAA. CNA used that experience to create the paper, Advancing Data Management at the FAA: Today and Tomorrow; A Holistic, Systematic Approach, describing our recommended systematic approach to advancing the practice of data management within the FAA.

Data Architecture

CNA analysts have experience in developing logical and physical data models that are used by new and existing systems of how data is represented and exchanged. CNA is also experienced in the data architecture field in the development of business rules that are applied to how data is arranged, exchanged, and stored by new and existing systems.

Aeronautical Information Exchange Model (AIXM)

CNA was instrumental in the creation of business process performance standards and data taxonomies to standardize and improve the error-free exchange of aeronautical information at the global level. We have led international efforts to define and provide technical standards and definitions of static and dynamic aeronautical information using common, international standards, such as the design and implementation of the Aeronautical Information Exchange Model (AIXM). We worked with the FAA to develop an aeronautical information ontology to support data mapping, modeling, traceability, and identification. We have played a critical role in the development and evolution of AIXM and its taxonomy extensions to support the effective collection and distribution of Notices to Airmen (NOTAMs) and Special Activity Airspace (SAA) definitions and schedules.

Data Governance

Data governance establishes processes that ensure that a set of data provided by a system can be trusted. CNA analysts have experience in developing business rules that are applied in the creation, collection, and exchange of data. CNA analysts have also developed constraints in the data model that help to ensure the quality of the data.


CNA provided support to establish data governance in the development of the Federal NOTAM System (FNS). We conducted analyses of the different scenarios that the FNS uses to understand the data collection and distribution requirements. This analysis was then used to develop the FNS data model, based on the AIXM. CNA analysts also developed the business rules used by the FNS to collect data from the data originators to reduce data errors and ensure the quality and integrity of the data.