Data stewardship is a fundamental practice in data management, the objective of which is to ensure proper handling of data assets and drive business to meet business objectives. It is comprised of practices and duties to maintain the accuracy, accessibility, and security of data over time. As companies continue to use data as a basis for decision-making, the role of data stewardship only becomes more critical.
Definition
Data stewardship is the management, administration, and oversight of an organization’s data assets to help provide business users with high-quality data that is easily accessible in a consistent manner. It is the determination of roles and responsibilities of people or teams responsible for data governance, data quality and data lifecycle management. Data steward are tasked with forming the policies and procedures that surround the quality, security, and availability of data.
Purpose
The primary purpose of data stewardship is to ensure that data is managed as a valuable organizational asset. This involves:
- Ensuring data quality and integrity.
- Facilitating data accessibility and usability.
- Protecting sensitive data from unauthorized access.
- Supporting compliance with regulatory requirements.
- Enhancing decision-making through reliable data.
By establishing clear data stewardship practices, organizations can maximize the value of their data while minimizing risks associated with data misuse or breaches.
How Data Stewardship Works
Data stewardship works by establishing a framework for managing data assets across the organization. This framework typically includes the following components:
1. Data Governance
Data governance provides the structure and control required for data management, including rules for data access and usage. It sets forth the responsibilities of data stewards and also provides for data quality assurance, data security, and data lifecycle management.
2. Data Quality Management
Data quality is a critical task of data stewards. This includes defining how data needs to be validated, cleansed and enriched to be accurate, complete and consistent. Data quality management also encompasses looking at data quality metrics and dealing with any of them that come up.
3. Data Security and Privacy
Data stewards are responsible for instituting safeguard measures to prevent unauthorized access to, breach of, and misuse of data. This involves the creation of access controls encryption and masking methodologies to protect sensitive data. Data stewards also comply with data protection laws – GDPR, CCPA and the like.
4. Data Lifecycle Management
Data lifecycle management is the process of managing the entire lifecycle of the data, from the time it is created and stored to the time it is archiving and then deleted. Data stewards are also responsible for maintaining data and disposing of it as per organisational policies and requirement by law.
5. Data Access and Usability
Data stewards also promote data accessibility by establishing mechanisms for data cataloging metadata stories and data sharing. They make sure that data is easily accessible and usable for approved users, driving data-based decision-making throughout the company.
Best Practices
To effectively implement data stewardship, organizations should follow these best practices:
1. Define Clear Roles and Responsibilities
Assign clear responsibilities to data stewards, data owners and data users. Make sure everyone knows their role and what they can do to help steward the data.
2. Develop a Comprehensive Data Governance Framework
Design a sound data governance programme that specifies policies, procedures and standards for managing data. Keep the framework relevant to the organizations goals, and any regulatory requirements.
3. Implement Data Quality Processes
Design mechanisms for validating, cleaning, and enriching data to ensure good data quality. Monitor quality metrics routinely and remediate anomalies when detected.
4. Ensure Data Security and Privacy
Maintain robust security to store sensitive data securely. Comply with data privacy laws and reevaluate security measures on a regular basis.
5. Foster a Data-Driven Culture
Establish a culture of data-informed decision-making by educating and empowering staff to see data stewardship as part of their role. Facilitate cooperation and coordination among data stewards, its users, and other related partners.
FAQs
A data steward is responsible for managing and overseeing an organization’s data assets. This includes ensuring data quality, security, and accessibility, as well as implementing data governance policies and procedures.
Data stewardship is important because it ensures that data is managed as a valuable organizational asset. It helps maintain data quality, protect sensitive information, and support data-driven decision-making.
Data stewardship supports compliance by ensuring that data management practices align with regulatory requirements. This includes implementing data privacy measures and maintaining accurate records of data processing activities.
The key components of data stewardship include data governance, data quality management, data security and privacy, data lifecycle management, and data access and usability.
Organizations can improve data stewardship by defining clear roles and responsibilities, developing a comprehensive data governance framework, implementing data quality processes, ensuring data security and privacy, and fostering a data-driven culture.
Related Terms
- Data Governance
- Data Quality Management
- Data Security
- Data Privacy
- Data Lifecycle Management
- Data Cataloging
- Metadata Management
- Data-Driven Decision-Making