Data steward

Definition

A data steward is an individual responsible for managing and overseeing an organization's data assets to ensure data quality, integrity, and accessibility. This role is crucial in maintaining the trustworthiness of data throughout its lifecycle, supporting compliance with regulations and ethical standards.

5 Must Know Facts For Your Next Test

1. Data stewards play a key role in implementing data governance policies and ensuring that data is used responsibly within the organization.
2. They are often tasked with monitoring data quality metrics and addressing any issues that may arise, such as inaccuracies or inconsistencies in the data.
3. In the context of AI, data stewards help ensure that training datasets are ethically sourced and representative to avoid bias in AI models.
4. Data stewards collaborate with various teams, including IT, compliance, and business units, to promote best practices for data management.
5. Their responsibilities also include educating employees about data policies and the importance of maintaining high data quality standards.

Review Questions

• How does the role of a data steward contribute to the overall data governance strategy within an organization?
  • A data steward is integral to a data governance strategy as they implement policies and ensure adherence to standards regarding data management. They serve as a bridge between different teams, facilitating communication and ensuring that everyone understands the importance of maintaining high-quality data. By overseeing data practices and ensuring compliance with regulations, they help build trust in the organization's data assets.
• Discuss how a data steward can address potential biases in AI by managing training datasets.
  • A data steward plays a crucial role in mitigating biases in AI by ensuring that training datasets are diverse and representative of the population. By actively monitoring the sourcing and composition of these datasets, they can identify potential imbalances or biases that could lead to unfair outcomes. Their oversight ensures that AI systems are developed using ethical practices, which is vital for fostering trust and accountability in AI solutions.
• Evaluate the long-term impacts of having effective data stewardship on organizational decision-making processes.
  • Effective data stewardship leads to improved decision-making processes by ensuring high-quality, reliable data is readily available to decision-makers. With accurate and well-managed data, organizations can make informed choices that align with their strategic goals. Additionally, strong stewardship fosters a culture of accountability regarding data usage, enhancing transparency and fostering a more ethical approach to decision-making in the organization over time.

Related terms

Data Governance: The framework that establishes the policies, procedures, and standards for managing data assets within an organization.

Data Quality: The condition of a dataset, typically measured by its accuracy, completeness, reliability, and relevance for its intended use.

Data Management: The practice of collecting, storing, organizing, and maintaining data to ensure its availability and usability.