What is data stewardship?
Data stewardship is the management and oversight of an organization's data assets, which helps provide business users with high-quality, easily accessible and consistent data. While data governance focuses on high-level policies and procedures, data stewardship focuses on tactical coordination and implementation.
Data stewards are responsible for data use and security policies determined by enterprise data governance initiatives. They typically are the liaison between the IT department and the business side of an organization.
The role requires various technical and business skills, including programming and data modeling. Data stewards are also versed in areas such as data warehousing, storage and enterprise strategy. Strong communication and collaboration skills are required for the role.
Some organizations have created formal data steward positions, often filling them with people drawn from various business units. Others assign stewardship responsibilities to employees who also have other duties.
A data steward might function as a data coordinator, who tracks data movement inside an organization, and a data corrector, who understands and enforces internal rules on how data can be used. Regardless of how the position is structured, an effective data steward maintains agreed-upon data definitions and formats, identifies data quality issues and ensures that business users adhere to specified data standards.
An organization might have a data stewardship program as part of its overall data lifecycle management effort or to help with data quality improvement projects. A data steward often collaborates with data architects; business intelligence developers; extract, transform and load designers; business data owners; and others to uphold data consistency and quality metrics. Data quality tools and data profiling software are key technology components of many data stewardship programs.
Why is data stewardship important?
The data steward position -- and, in fact, information governance overall -- emerged as a critical role in the second decade of the 21st century. At that time, data and the information it yields started becoming more valuable. Organizations increasingly rely on data and the insights gleaned from it to make strategic decisions, drive tactical activities and support digital transformation efforts.
Data must be accurate, current and accessible to executives, managers and line workers when and where they need it. This enables them to make data-driven decisions. Accurate and accessible data also drives technology initiatives, such as machine learning and artificial intelligence (AI) programs that depend on data to work.
Roles and responsibilities of a data steward
Data steward responsibilities include inventorying corporate data, determining how to access it and identifying where it's needed. They typically are tasked with ensuring its accuracy and availability. However, data steward responsibilities can also include helping to identify and articulate ways to use company data to create competitive advantages in the market.
The roles and responsibilities of a data steward vary based on the maturity of the data program within an organization. For data stewards whose positions are new to an organization and where data governance is in its early stages, their duties might be tasks aimed at consolidating data from multiple databases and platforms. They might also be charged with establishing processes to manage data best.
Data stewards at companies with more mature data programs, where that foundational work has been done, are typically focused on higher-value tasks. These can include ensuring the quality of the data, managing compliance with data standards and policies as established by the governance program, and advocating for data use cases within the business.
In general, data stewards' duties include the following:
- Managing data from a variety of sources.
- Guaranteeing the quality of the data the organization collects, stores and uses.
- Documenting and enforcing rules around data collection, storage and use.
- Executing the policies and standards in the organization's data governance program.
- Ensuring access to the right data by the right users at the right time based on whether information is private, corporate or sensitive.
- Helping to create and implement processes and procedures for data collection, storage, use and security.
- Identifying ways to use data to drive enterprise objectives.
Data stewards are accountable for managing all data collected and used by the enterprise and ensuring that the data-related rules established by the data governance program are followed.
What are the benefits of data stewardship?
Data stewardship programs help organizations in several ways. The following are some of the benefits of a data stewardship program:
- Improved data quality.
- Better data documentation.
- Clear, concise data policies and processes.
- Efficient and effective analytics programs.
- Frequent use of data to make decisions.
- Improved compliance with data-related regulations.
- Fewer errors in processes and decisions driven by data.
- Reduced risks around data-related security and privacy requirements.
Challenges of data stewardship
Data stewardship involves several challenges, including the following:
- Privacy and confidentiality. Data stewards must protect sensitive customer data, such as personal details, in a data domain regulated by protections such as the European Union's General Data Protection Regulation.
- Inconsistent data quality. Variations in data quality across systems or departments can degrade data integrity, making it difficult for stewards to standardize and maintain reliable data governance.
- Resource limitations. Stewardship requires organizational investment in time, tools and skilled staff. If the proper investments aren't made, data custodians might be unable to manage large, complex data domains.
- Resistance to change. Employees or teams might resist adopting new processes and tools outlined in the framework, slowing efforts to implement best practices.
- Compliance issues. Data stewards must adapt quickly to constantly shifting legal and industry standards to avoid costly governance gaps. The cost of a data breach in 2024 was $4.88 million, according to IBM.
Uses of a data stewardship program
An organization might have a single data steward or multiple professionals in this role. How it does this depends on its size, the criticality of its data needs, the maturity of its data program, its industry and its business objectives. Organizations with multiple data stewards might assign them to business units or certain data types.
Uses of a data stewardship program include oversight and management of the following:
- Enterprise data efforts and operations, including data lifecycle management, which establishes and enforces how long data is retained.
- Data quality programs, including establishing and using quality metrics and quality detection and correction procedures.
- Data privacy, security and risk management according to standards set in conjunction with the data governance program, the security team, the legal department and the risk function, including the implementation and monitoring of controls.
- Enterprise policies and procedures for accessing data to ensure authorized users have access to data at the time and in the format they need it, and in a way that ensures the confidentiality and integrity of the data.
The data stewardship program works in conjunction with the data governance program. Data governance is the group that sets the enterprise's objectives, risk tolerance, security requirements and strategic needs regarding data.
Data stewards also work with the organization's data owners, who are typically senior managers and department heads responsible for identifying the data their respective functions need and understanding how their functions will use data to achieve the business's goals. The data can include corporate data and data obtained elsewhere.
Data steward vs. data analyst vs. data scientist
Organizations with data stewards expect them to work closely with the data analysts and data scientists who access and analyze data to understand past trends, identify patterns and predict future outcomes.
While all three professionals handle data, data stewards aren't the same as data analysts and data scientists. Data analysts and scientists retrieve and organize data to analyze and manipulate it to gain insights and draw conclusions.
They use data to produce reports on an organization's performance and current state, helping business leaders make data-driven decisions.
Data analysts and scientists use data to glean insights into future outcomes. They also use data for predictive analytics, such as determining the most likely outcomes as they change and adjust different variables within the scenario.
Organizations must use data to remain competitive. Industries such as banking and retail see data as critical to delivering services and goods. Moreover, some industries see their use of data as central to their existence. Health systems, for instance, increasingly rely on data and analytics to ensure the best patient outcomes. In addition, emerging fields, such as robotics and AI, exist solely because of the data they're built on. These factors make data stewards an essential part of a modern enterprise team.
Data stewardship vs. data governance
Data stewardship involves hands-on data management. Successful data stewardship ensures accuracy, accessibility and quality within a specific data domain, such as customer records or financial metrics. It also ensures that data aligns with business needs and remains reliable for decision-making.
On the other hand, data governance involves creating the larger governance framework that data stewards adhere to. This includes defining policies, standards and data governance rules across an organization. Data governance is the overarching system that outlines who owns data, how it's used and what best practices must be enforced. Data stewards put all this into action within specific domains, such as customer insights or operational logs.
Data stewardship is part of the enterprise's overall data governance framework. Learn about the top data governance tools.
