Data stewards

Data stewards are vital professionals within an organization responsible for the practical, day-to-day oversight and management of its data assets. They ensure that data is accurate, accessible, secure, and compliant with relevant regulations and internal policies. This role operates under the broader umbrella of data governance, a financial category focused on establishing policies and processes for managing data throughout its lifecycle. Data stewards bridge the gap between high-level data governance policies and their operational implementation, ensuring data is usable and trusted for decision-making.

What Are Data Stewards?

Data stewards are designated individuals or groups responsible for managing and overseeing an organization's data to ensure its integrity, usability, and compliance. This role falls under the financial category of data governance, which establishes the overall framework and policies for how data is handled. Unlike data governance, which sets the broad standards, data stewardship focuses on the hands-on implementation and enforcement of these policies on a daily basis. Data stewards act as custodians of data, overseeing its lifecycle from creation to disposal, ensuring that data remains of high data quality and is used ethically²⁵. Their responsibilities often include defining metadata, ensuring proper data lineage, and classifying sensitive information²⁴.

History and Origin

The concept of data stewardship evolved as organizations recognized the critical importance of managing their burgeoning data effectively. In the early 2000s, as enterprises increasingly adopted complex systems like Enterprise Resource Planning (ERP), the necessity for robust data management became evident. Poor data quality in these systems could cripple operations, leading to increased costs and lost revenue²³.

The formalization of data stewardship as a distinct role gained significant momentum with the publication of influential frameworks. The Data Management Body of Knowledge (DAMA-DMBOK), first released in 2009 by DAMA International, played a pivotal role in standardizing and elevating the awareness of data stewardship as a critical component of comprehensive data management²²,²¹. The DAMA-DMBOK defined data stewardship as a role that ensures data content and metadata align with organizational policies, standards, and business rules, thereby achieving an appropriate level of data quality for effective use²⁰. This framework helped establish data stewards as operational enablers who carry out day-to-day activities to uphold data governance standards¹⁹.

Key Takeaways

• Data stewards are responsible for the daily, operational management of data assets, implementing policies set by data governance.
• Their primary goal is to ensure data quality, accessibility, security, and compliance with regulations.
• Data stewards define data quality metrics, manage metadata, trace data lineage, and classify sensitive data.
• They serve as a crucial liaison between business units and IT, fostering communication and collaboration around data use.
• The role has evolved significantly with the rise of data-driven decision-making, artificial intelligence, and stringent data privacy regulations.

Interpreting the Data Stewards Role

The role of data stewards is interpreted through their practical impact on an organization's data landscape. They are central to ensuring that data is trustworthy and fit for its intended purpose, which is crucial for informed business decisions and analytical insights. Data stewards implement the rules and standards set by the overall data governance framework, transforming high-level policies into actionable procedures¹⁸.

They are responsible for maintaining agreed-upon data definitions and formats, identifying and resolving data quality issues, and ensuring that business users adhere to specified data standards¹⁷. In essence, data stewards ensure that data is not just collected but is also reliable, consistent, and available to the right users at the right time, thereby enhancing the organization's ability to leverage its data assets effectively¹⁶.

Hypothetical Example

Consider a large financial institution, "Global Bank Corp," implementing a new customer relationship management (CRM) system. The project involves migrating vast amounts of customer data, including personal details, transaction history, and investment portfolios. To ensure the success of this migration and the ongoing accuracy of data, Global Bank Corp assigns several data stewards to different business units, such as retail banking, wealth management, and commercial lending.

A data steward for the retail banking unit is tasked with overseeing customer demographic data. Their responsibilities include:

1. Defining Data Standards: Working with business users to clarify what constitutes a "valid" customer address or phone number, establishing formatting rules, and identifying acceptable data sources.
2. Monitoring Data Quality: Using data profiling tools to identify inconsistencies or errors in existing customer records before and after migration. For example, they might find multiple entries for the same customer with slightly different spellings or addresses.
3. Resolving Discrepancies: Collaborating with IT to implement automated data cleansing rules and manually reviewing complex cases of mismatched customer data. They might work with customer service representatives to verify information directly with clients.
4. Ensuring Compliance: Verifying that the collection, storage, and usage of sensitive customer information adhere to data privacy regulations like the California Consumer Privacy Act (CCPA) and General Data Protection Regulation (GDPR). They ensure that only authorized personnel have access to certain data fields.
5. Documenting Metadata: Maintaining comprehensive documentation about where customer data originates, how it's transformed, and its current status, which helps establish clear data lineage.

Through these actions, the data steward ensures that the customer data in the new CRM system is highly accurate and reliable, enabling Global Bank Corp to provide better customer service and comply with stringent regulatory compliance requirements.

Practical Applications

Data stewards are integral to many facets of modern business operations, particularly in sectors heavily reliant on data. Their practical applications span various areas:

• Financial Services: In finance, data stewards ensure the accuracy and consistency of financial data, which is critical for reporting, risk management, and regulatory compliance (e.g., Basel III, Dodd-Frank)¹⁵. They help maintain the integrity of customer accounts, transaction records, and market data.
• Healthcare: Data stewards manage sensitive patient information, ensuring adherence to privacy regulations like HIPAA and maintaining the quality of electronic health records for accurate diagnoses and treatment.
• Retail and E-commerce: They oversee customer purchase histories, inventory levels, and supply chain data, supporting targeted marketing efforts and efficient operations.
• Data Migration and Integration Projects: During system upgrades or mergers, data stewards are crucial for validating and reconciling data from disparate sources, ensuring seamless transitions.
• Artificial Intelligence (AI) and Machine Learning Initiatives: High-quality, well-governed data is the foundation for effective AI and ML models. Data stewards ensure the data used for training these models is accurate, unbiased, and properly prepared, leading to more reliable analytical outcomes¹⁴,¹³. For instance, the National Institute of Standards and Technology (NIST) has been developing a Data Governance and Management Profile to help organizations harmonize their privacy, cybersecurity, and AI frameworks, underscoring the importance of roles like data stewards in these integrated efforts¹².

Limitations and Criticisms

While essential, the role of data stewards can face certain limitations and criticisms. One common challenge is that the effectiveness of data stewards often hinges on the maturity of an organization's overall data governance program. Without clear policies, strong executive sponsorship, and adequate resources, data stewards may struggle to enforce standards or gain the necessary cooperation from various departments¹¹.

Another limitation can be the ambiguity of their authority. Data stewards typically enforce policies rather than create them, and they may not always have the direct power to mandate changes in data practices across different business units. This can lead to resistance or slow adoption of data quality improvements if there is a lack of understanding or perceived burden from other teams. Furthermore, the sheer volume and complexity of data in modern enterprises can overwhelm data stewards, making comprehensive oversight challenging, especially without robust automation and technology tools¹⁰.

There can also be a critique related to the dual nature of the role—some data stewards might have other primary responsibilities, meaning data stewardship is an add-on rather than a dedicated function. This can lead to insufficient time or focus being allocated to data quality and governance activities. ⁹As data privacy regulations continue to evolve globally, ensuring regulatory compliance becomes increasingly complex, requiring data stewards to constantly adapt and stay informed of new requirements, which can be a significant burden.
⁸

Data Stewards vs. Data Owners

While often discussed together within data management and data governance frameworks, data stewards and data owners hold distinct responsibilities. A data owner is typically a senior business leader or executive who has ultimate accountability and approval authority for specific data assets within their domain. ⁷They define the strategic importance, policies, and standards for the data. For example, the Head of Marketing might be the data owner for customer demographic data, responsible for ensuring its strategic value and compliance.

In contrast, a data steward is a designated individual or team responsible for the operational implementation and enforcement of the policies established by the data owner and the broader data governance framework. ⁶Data stewards are more hands-on, focusing on the day-to-day tasks of ensuring data quality, consistency, and adherence to rules. ⁵They act on behalf of the data owner to maximize the data's intended value. ⁴The data owner sets the "what" and "why," while the data steward handles the "how" and "when."

FAQs

What skills are essential for data stewards?

Effective data stewards require a blend of business acumen and technical understanding. Key skills include strong communication and collaboration, analytical abilities for identifying data quality issues, problem-solving, attention to detail, and a foundational understanding of databases, data modeling, and relevant data privacy regulations.
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How do data stewards contribute to an organization's financial success?

By ensuring high data quality and reliable data assets, data stewards enable better data-driven decision-making, reduce operational inefficiencies caused by poor data, mitigate risk management by ensuring compliance, and support advanced analytics initiatives like artificial intelligence, all of which contribute to improved financial outcomes and competitive advantage.
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Is data stewardship a full-time role?

Data stewardship can be a full-time, dedicated role in larger organizations, or it can be assigned as a responsibility to employees who have other primary duties, particularly in smaller entities. ¹The structure often depends on the complexity of the organization's data landscape and the maturity of its data governance program.