Data Stewardship: Managing a Valuable Asset

As data becomes increasingly central to business operations, so does the importance of its quality, security and accessibility. Data stewardship ensures data is being used to generate business value while maintaining compliance with regulatory standards and organizational policies regarding its use.  In this article, we’ll explore the role of the data steward and how this function fits into the data governance framework.

What Is Data Stewardship? 

Data stewardship refers to managing and overseeing an organization's data assets throughout the data lifecycle. It involves a set of practices that support the strategic, responsible use of business data. Data stewards, the data professionals tasked with ensuring that these priorities are met, have two primary responsibilities:  actively promoting the use of an organization’s data assets in ways that leverage its value, and maintaining compliance with relevant ethical and regulatory requirements in the ways that data is collected, stored and used.

In most organizations, data stewardship isn’t the responsibility of a single person. Instead, multiple data stewards take ownership of different data domains. Data stewards are skilled data managers with strong communication skills, providing technical expertise and the ability to collaborate with diverse data users. 

Data stewardship versus data governance

Data stewardship is an essential component of data governance. A data governance program provides a broad framework of processes, policies and metrics required for data management. Data stewardship focuses on the practical outworking of data governance standards and executing tasks such as managing data quality and access. 

Functions of Data Stewardship in Data-Driven Businesses

Organizations prioritizing data stewardship ensure that data is managed, maintained and used effectively. Data stewardship involves a variety of initiatives and tasks. 

Data quality assurance

One of the primary purposes of data stewardship is to maintain data quality. Data stewards actively monitor data quality metrics so users can depend on the integrity of their data. When quality issues are detected, data stewards play an active role in resolving them.

Documentation and metadata management

Data stewards document data processes, data dictionaries and other relevant information to make it easy for users to understand the data landscape within the organization. They also maintain metadata, which includes information about data definitions, relationships and data lineage. This metadata helps users understand the context and origin of the data they are working with.

Access monitoring and data security

Many organizations have a large number of data users, with each accessing and applying data resources to fulfill their roles within the company. Verifying that these interactions remain compliant with established standards is essential to data stewardship. Data stewards actively track how an organization’s data is being used and identify potential threats, including attempts to bypass access control methods, unauthorized use or disclosure of sensitive data and data exfiltration. Data stewards may also oversee security measures such as data anonymization, encryption and data breach response plans. 

Improved regulatory compliance

Many organizations routinely handle sensitive data subject to government regulations such as GDPR, CCPA and HIPAA. Data stewards are tasked with actively monitoring and enforcing compliance with these standards, industry regulations and internal policies.

Streamlined data access and cross-team collaboration

Data stewards act as a bridge between teams, facilitating communication and collaboration among data users, analysts and IT teams. This helps ensure everyone is on the same page regarding data definitions, usage and changes. Data stewards may also provide training and educational resources to teams to improve data literacy and the understanding of data management best practices.

Promote new data use cases

Due to the nature of their work, data stewards are organizational data experts. Data stewards use this familiarity with available data to discover and promote new ways to use data resources to generate additional value. As the needs of the organizations evolve, data stewards ensure an organization’s data strategy remains relevant. 

How Snowflake Supports Data Stewards

Snowflake provides industry-leading data governance features that support data stewardship best practices. A suite of capabilities enables data stewards and other data governance professionals to implement the highest levels of governance for data stored and accessed in Snowflake. 

Column- and row-level security

Column-level security in Snowflake allows a masking policy to be applied to a column within a table or view, ensuring its visibility only to those authorized to work with it. Row-level security works in a similar way, allowing the application of a row access policy to a table or view to determine which rows are visible in the query result.

Object tagging and tag-based masking policies

Tags enable data stewards to carefully monitor sensitive data for compliance, discovery, protection and resource usage use cases through either a centralized or decentralized data governance management approach. Using object tagging, those entrusted with data stewardship responsibility can track sensitive data for compliance, discovery, protection and resource usage.  A tag-based masking policy provides an additional option for securing sensitive data, enabling the protection column data by assigning a masking policy to a tag and then setting the tag on a database object or the Snowflake account.  When the data type in the masking policy signature and the data type of the column match, the tagged column is automatically protected by the conditions in the masking policy. This feature simplifies the data protection efforts because column data that should be protected no longer needs a masking policy manually applied to the column to protect the data.

Data classification

Data classification allows data stewards or others responsible for data governance to categorize potentially personal and/or sensitive data to support compliance and privacy regulations. Classification functions associate Snowflake-defined tags (i.e., system tags) to columns by analyzing the cells and metadata for personal data, making this data trackable. Using tracking information and related audit processes, teams can protect the column containing personal or sensitive data with a masking policy or the table containing this column with a row access policy. These processes can be used to support compliance with data privacy regulations.

Access history

Data stewardship has a heavy emphasis on security and compliance. The access history feature allows the auditing of the user access history. The records displayed in this view streamline regulatory compliance auditing while providing insights on popular and frequently accessed tables and columns.

Data lineage

Data lineage enables businesses to ensure the data they rely on remains high-quality, accurate and consistent. Data lineage is the process of documenting the data life cycle. It’s a set of practices that provides organizations with clear visibility into the origins of their data and how that data is transformed, aggregated and/or otherwise manipulated as it transits between systems and processes. With Snowflake Horizon, organizations can attain enhanced compliance through additional certifications, data quality monitoring and lineage.  Snowflake’s new Data Lineage UI (now in private preview) gives customers a bird’s-eye view of the upstream and downstream lineage of objects — making it easy to see how downstream objects may be impacted by modifications that happen upstream.

Empower Your Data Stewards with Snowflake Horizon

Horizon, Snowflake’s built-in governance solution, provides a unified set of compliance, security, privacy, interoperability and access capabilities in the Data Cloud. Using Snowflake Horizon, organizations gain a suite of essential data governance capabilities, including advanced privacy policies and secure, cross-cloud data sharing. Data stewards and other data governance experts can implement robust platform security and data security capabilities include authentication, encryption, continuous risk monitoring and protections, role-based access control and granular authorization policies, helping them maximize the value of their data while ensuring its integrity and security.