Critical Data Elements Best Practices for Data Governance

By Rob Aldridge

Published on July 11, 2024

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. 

Slide covering why CDEs are important per APRA in Australia from an Alation presentation.

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.

Slide from DGX showing their Critical Data Element Framework

What’s the CDE framework for data governance?

Listeners were taught that the CDE framework for data governance involves three key steps:

  1. Identify CDEs related to critical business processes, key reports and dashboards, and regulatory reporting requirements. 

  2. Formalise those CDEs through definitions and a repository of resources. 

  3. Work CDEs into effective data governance efforts by creating processes to manage:

    1. Data lineage to understand where data is created, how it moves through the organisation and systems, and any transformations along the way. 

    2. Data controls to assess and reduce risks.

    3. 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.

Slide sharing how customers use Alation to support Critical Data Elements (CDEs) per APRA

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
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