Data governance is a key component of a robust data culture. As more regulations mandating increased responsibilities around the management, control, and processing of data emerge, organisations have invested more resources in data governance efforts.
But there are only so many hours in the day, which requires data governance teams to focus their efforts. Enter critical data elements, better known as CDEs, which are data deemed essential for the success of a given organisation, capability, or outcome.
Regulators have now turned their attention to CDEs to ensure effective data management and data governance, making your organisation’s approach to CDEs even more important. In fact, APRA released “six factors for businesses to consider” related to data management,” one of which is, “Identify critical data elements and create a consistent set of data controls.”
In a recent webinar, Mastering Critical Data Elements: A Blueprint for Modern Data Governance, Chad Barendse, data governance expert, dissected the crucial nature of CDEs for modern data governance and provided a detailed framework for identifying and managing CDEs in any organization.
Barendse was joined by Tim Moon, Founder and Principal of DGX, Australia’s leading provider of Data Governance education and advisory services, and myself, Rob Aldridge, Senior Sales Engineer at Alation in Melbourne.
Below is a short summary of Barendse’s insights on this increasingly relevant topic. For the full discussion on CDEs and the CDE framework, plus a demonstration of how Alation enables CDE through data governance, watch the on-demand webinar replay.
The significance of CDEs
CDEs are the data that informs and enables an organisation’s operations, decision-making processes, risk management, reporting accuracy, and compliance with regulatory requirements. Think customer names, prices, dates, and other data that is used to make decisions and comply with regulatory requirements. Or, from the opposite perspective, it’s data that, if unavailable or untrustworthy, would severely impact the organisation.
Organisations have used those benchmarks as ways to determine if specific data is a CDE.
As Barendse explains, CDEs have grown in importance as governing bodies and data-focused entities added CDEs to various data governance frameworks, principles, and regulations. In 2019, the Australian Prudential Regulation Authority (APRA) launched a pilot with the country’s key financial services and banking firms to identify their 100 most critical data elements. From there, the firms were empowered to create more effective management of those data elements. One outcome of that pilot is Prudential Standard CPS230, which aims to strengthen operational risk management for APRA-regulated entities.
Once you understand your CDEs, Barendse says, it’s easier to focus data governance efforts.
How do CDEs ease data governance efforts?
Prioritising data by importance, since not all data is critical to business success or regulatory compliance.
Identifying data required for regulatory compliance.
Improving data quality where it will provide the most impact to the organisation.
Focusing risk management efforts with more effective data governance.
Assigning accountability over different data elements.
Increasing visibility of critical data.
Creating a systematic approach to managing critical data.
By prioritising important data, ensuring regulatory compliance, and improving data quality, CDEs help businesses focus their risk management strategies and assign accountability. This systematic approach not only increases the visibility of essential data but also fosters a more efficient and effective data management framework.
Using a CDE framework to improve data governance
Regulated businesses and industries are generally familiar with CDEs and data governance efforts because they are required. But that doesn’t excuse unregulated entities from following and learning from this approach to improve data governance.
Barendse uses a framework he terms “the gold standard of implementing CDEs.” It’s a simple guide that can help you identify and formulate CDEs, and then build the proficiency to track the data journey, control how data is used, and ensure data quality along the way.
What’s the CDE framework for data governance?
Listeners were taught that the CDE framework for data governance involves three key steps:
Identify CDEs related to critical business processes, key reports and dashboards, and regulatory reporting requirements.
Formalise those CDEs through definitions and a repository of resources.
Work CDEs into effective data governance efforts by creating processes to manage:
Data lineage to understand where data is created, how it moves through the organisation and systems, and any transformations along the way.
Data controls to assess and reduce risks.
Data quality for data completeness, conformity, consistency, timeliness, and validity.
Barendse stresses the importance of using this framework in a systematic, repeatable way. Your CDEs will likely change across departments, business units, and related entities. Using and reusing a solid framework will make data governance much easier, faster, and less stressful for your organisation.
Also important, Barendse says, is the actual execution of data governance via a centralised, federated, or hybrid model based on your organisation’s needs and data culture. Traditional data governance uses centralised control and management of data assets. Federated data governance implements governance policies and controls in a decentralised fashion while maintaining coordination and consistency across domains. A hybrid approach combines the two.
How a data catalog improves CDE management and data governance
The Alation data intelligence platform helps organisations manage and integrate CDEs seamlessly into data governance workflows. It provides a repository for data element descriptions, classifications like for personally identifiable information (PII), risk levels, and other attributes, creating a library of data definitions for a shared, transparent view of your organisation’s CDEs. Alation also enables workflows for data governance approvals to ensure definitions, categorizations, and other attributes are properly inputted and vetted.
For any data, CDEs and otherwise, Alation further allows teams to tag data stewards and subject matter experts to improve data utilisation and data cultures and track data lineage back to the original data source or down to the reporting tools used to present the data.
Effective CDE management and data governance requires more than spreadsheets and email. The Alation data intelligence platform supports data governance success even in a shifting data landscape.
To see how Alation enables CDE management, skip to the 22:00 mark on the webinar replay to see a short product demonstration. Or, schedule a personalised Alation demo today.
- The significance of CDEs
- How do CDEs ease data governance efforts?
- Using a CDE framework to improve data governance
- How a data catalog improves CDE management and data governance
Contents
FAQs
What is a critical data element (CDE)?
Critical Data Elements, also known as CDEs, are the data that informs and enables an organisation’s operations, decision-making processes, risk management, reporting accuracy, and compliance with regulatory requirements.
How do critical data elements (CDEs) improve data governance efforts?
By prioritising important data, ensuring regulatory compliance, and improving data quality, CDEs help businesses focus their risk management strategies and assign accountability. This systematic approach not only increases the visibility of essential data but also fosters a more efficient and effective data management framework.
What is the Critical Data Element (CDE) framework for data governance?
Identify Critical Data Elements (CDEs) related to critical business processes, key reports and dashboards, and regulatory reporting requirements.
Formalise those CDEs through definitions and a repository of resources.
Work CDEs into effective data governance efforts by creating processes to manage:
Data lineage to understand where data is created, how it moves through the organisation and systems, and any transformations along the way.
Data controls to assess and reduce risks.
Data quality for data completeness, conformity, consistency, timeliness, and validity.
How does a data catalog improves critical data element (CDE) management and data governance?
A data catalog, like Alation's, provides a repository for data element descriptions, classifications like for personally identifiable information (PII), risk levels, and other attributes, creating a library of data definitions for a shared, transparent view of your organisation’s CDEs.
Why are regulators focusing on Critical Data Elements?
Regulators increasingly recognize that effective data governance requires prioritization—organizations cannot govern all data with the same level of rigor. By focusing on CDEs, regulators like APRA aim to ensure organizations properly manage the data most critical to financial stability, operational resilience, and regulatory compliance. This targeted approach acknowledges the practical constraints organizations face while still ensuring appropriate controls for essential data. APRA's 2019 pilot with financial services firms, which directed them to identify their 100 most critical data elements, exemplifies this pragmatic regulatory approach that balances comprehensive governance with implementation feasibility.
How do you identify which data elements qualify as CDEs?
Identifying CDEs requires evaluating data against clear criteria focused on business impact and regulatory requirements. Ask whether specific data elements are essential for critical business processes, key reports and dashboards, or regulatory reporting. Consider whether unavailability or inaccuracy of the data would severely impact operations, decision-making, or compliance. The identification process should involve both business and technical stakeholders to ensure all perspectives are considered. While the specific CDEs will vary across departments and business units, using consistent identification criteria creates a coherent approach to CDE management across the organization.
What role does data lineage play in CDE governance?
Data lineage is fundamental to effective CDE governance, providing visibility into how critical data flows through your organization. For CDEs, understanding lineage means tracking where data originates, how it moves between systems, what transformations it undergoes, and where it ultimately appears in reports or dashboards. This visibility enables impact analysis (understanding what would be affected by changes), supports audit requirements by documenting data provenance, and helps identify potential quality issues by revealing transformation points where errors might be introduced. A data catalog like Alation automates much of this lineage tracking, making it practical to maintain even in complex data environments.
How do different governance models affect CDE implementation?
Your governance model significantly influences how you implement CDE management. Traditional centralized governance places control with a central team that defines and enforces standards for CDEs across the organization. Federated governance distributes responsibility to domain experts while maintaining coordination through shared standards. Hybrid approaches combine elements of both models. The right choice depends on your organization's size, complexity, and culture. Regardless of model, successful CDE governance requires clear accountability, documented processes, and technology support through platforms like data catalogs to ensure consistency and visibility across the organization.
What benefits can unregulated businesses gain from implementing a CDE framework?
While regulatory requirements often drive CDE adoption in regulated industries, unregulated businesses can realize significant benefits from this approach. By identifying and properly managing critical data, these organizations can improve decision quality, reduce operational risks, enhance efficiency, and build stronger data cultures. The CDE framework provides a structured methodology for data prioritization that helps any organization focus limited resources where they'll deliver the greatest value. As data volumes continue to grow, even unregulated businesses need systematic approaches to identify what matters most—making the CDE framework valuable across all sectors.
How does Alation support the implementation of a CDE framework?
Alation's data intelligence platform provides comprehensive support for implementing and maintaining a CDE framework. The platform serves as a centralized repository for CDE definitions, classifications, and attributes, creating a shared understanding across the organization. Governance workflows enable proper vetting of changes to critical data definitions. Stewardship capabilities allow clear assignment of accountability for CDEs. Lineage tracking provides visibility into how critical data flows through systems. These capabilities move organizations beyond manual, spreadsheet-based approaches to create sustainable, scalable CDE governance programs that can adapt as data landscapes evolve and regulatory requirements change.
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