data stewardship

What is data stewardship?

Data stewardship is the management 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.

While data governance generally focuses on high-level policies and procedures, data stewardship focuses on tactical coordination and implementation.

A data steward is responsible for carrying out data usage and security policies as determined through enterprise data governance initiatives, acting as a liaison between the IT department and the business side of an organization.

The role requires a range of both technical and business-oriented skills, including programming and data modeling, as well as acumen in domains such as data warehousing and storage concepts and enterprise strategy. Strong communication and collaboration skills are also prized in data stewards.

Some organizations have created formal data steward positions -- in many cases, filling them with workers drawn from business units -- while others assign stewardship responsibilities to employees who have other duties as well.

A data steward might function as both a data coordinator, who tracks the movement of data 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.

A corporation may use a data stewardship program as part of its overall data lifecycle management effort and/or to help with data quality improvement projects. A data steward will often collaborate with data architects, business intelligence (BI) developers, ETL (extract, transform and load) designers, business data owners and others to uphold data consistency and data quality metrics. Data quality tools, including data profiling software, are key technology components of many data stewardship programs.

Why is a data steward important?

The data steward position -- and, in fact, information governance overall -- emerged as a critical role in the second decade of the 21st century as the value of data and the information it yields increased.

Organizations came to increasingly rely on data and the insights gleaned from it to make strategic decisions and drive tactical everyday activities, fueling their transformation into digital operations.

As such, data needed to be accurate, current and accessible to executives, managers and line workers when and where they needed it so they could make data-driven decisions. Organizations also came to need accurate and accessible data to fuel technology initiatives such as machine learning and artificial intelligence (AI) programs that are dependent on data to work.

Data stewards, with responsibility for inventorying corporate data, how to access it and where it's needed, are thus typically tasked with ensuring its accuracy and availability. But data steward responsibilities can also include helping to identify and articulate ways to utilize corporate data to create competitive advantages in the market.

What are the roles and responsibilities of a data steward?

The roles and responsibilities of a data steward can vary based on the maturity of the data program within an organization.

The duties for data stewards whose positions are new to an organization and where data governance is in its early stages may center on tasks aimed at consolidating data from multiple databases and platforms and establishing processes to best manage data moving forward.

Data stewards at companies with more mature data programs, where that foundational work has already been done, are typically focused on higher-value tasks, such as ensuring the quality of the data, managing compliance to the 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 gathered, stored and used by the organization;
• documenting and enforcing rules around data collection, storage and use;
• executing the policies and standards established by the data governance program;
• ensuring access to the right data by the right users at the right time based on whether information is private data, corporate data or sensitive data, etc.;
• helping to create and implement processes and procedures for data collection, storage, use and security; and
• helping to identify ways to use data to drive enterprise objectives.

In summary, data stewards are accountable for the management of all data within and used by the enterprise and ensuring that the data-related rules as established by the data governance program are followed.

What are the benefits of data stewardship?

Data stewardship programs help organizations in a number of ways. The benefits of a data stewardship program include the following:

• improved data quality;
• better data documentation;
• clear, concise data policies and processes;
• more efficient and effective analytics programs;
• more frequent use of data to make decisions;
• improved compliance with data-related regulations;
• fewer errors in processes and decisions that are driven by data; and
• reduced risks around data-related security and privacy requirements.

Uses of a data stewardship program

An organization may have a single data steward, or it may have multiple professionals working in this role, depending on the size of the organization, the criticality of its data needs, the maturity of its data program, its industry and its business objectives. Organizations with multiple data stewards may opt to assign them to business units or departments or to certain types of data.

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 the establishment and use of 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; and
• enterprise policies and procedures for accessing data, with the goal of ensuring authorized users have access to needed data at the time and in the format they need it in and in a manner that also ensures the confidentiality and integrity of the data.

The data stewardship program works in conjunction with the data governance program, the body that sets the enterprise's objectives, risk tolerance, security requirements and strategic needs relating to 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, as well as for understanding how their functions will utilize that data to achieve the goals established by the enterprise. The data identified by data owners includes corporate data and data that is obtained elsewhere.

Data steward vs. data analyst

Similarly, organizations with data stewards expect them to work closely with the data analysts and data scientists who access and analyze data to unearth past trends, identify current patterns and predict future outcomes.

While all three of these positions handle data, data stewards are not the same as data analysts and data scientists.

Data analysts and data scientists retrieve and organize data in order to analyze and manipulate it to draw conclusions and insights.

They use data to produce reports on an organization's past performance or current state, thereby helping organizational leaders make data-driven decisions.

Data analysts and data scientists also use data to glean insights about future outcomes; additionally, they use data for predictive analytics, i.e., determining the most likely outcomes as they change and adjust different variables within the scenario.

Organizations today have to use data in order to remain competitive, with some industries such as banking and retail seeing data as critical to their ability to deliver services and goods. Moreover, some industries see their use of data as central to their existence. Health systems, for instance, rely more and more on data and analytics to ensure the best outcomes for patients. In addition, there are emerging fields, such as robotics and AI, that exist solely because of the data that fuels their movements. All of which makes data stewards an essential part of a modern enterprise team.