Data Stewardship
Data stewardship is a collection of functions and approaches that encompass the definition, implementation, and maintenance of information standards across an organization's data stakeholders. It provides the framework and support mechanisms that are required to help data stakeholders meet with and adhere to compliance requirements, internal policies, and strategic objectives in accordance with data governance programs. The people, processes, and structure that comprise data stewardship ensure the effective management of information resources on behalf of others and for the best interests of an organization.
A data steward is responsible for making sure that an organization’s data is managed and ready to use. As the name implies, this individual stands watch over data collection and usage policies. Data stewards do not develop information management policies, but rather implement and enforce them across an organization.
The job of a data steward is expansive. The role involves planning, deploying, and managing the sourcing, use, and maintenance of data assets within an organization. Data stewards enable an organization to take control and govern all the types and forms of data along with associated storage.
Importance of a Data Steward
Data stewards are of vital importance as they act as the intermediaries for top-level data goals, roles, and requirements for data and the people who produce, protect, and use it. They maintain the balance of standards and agility. Data stewards work across all levels of an organization to put in place the right combination of processes and protocols for optimum efficiency and efficacy related to all aspects of data.
The Role and Responsibilities
At a high level, a data steward’s responsibility is to ensure that there are documented procedures and guidelines for data access and use. A data steward’s role includes:
- Helping to plan and execute data governance, control, and compliance policies
- Understanding the organization and the interaction of processes with data entities and elements
- Maintaining an inventory of all data and where it resides
- Providing guidance on whether data can be trusted based on its quality and source
- Managing data access based on rights and regulations
- Establishing naming standards
- Enforcing rules around data
- Optimizing data workflows
- Facilitating compliance and data security
- Creating definitions for data entities
- Setting up data security specifications
- Analyzing data to identify problems
- Recommending ways to improve data quality
An effective data steward is a dynamic person who can engage with colleagues in all departments and at all levels of an organization. A data steward should also have the following qualifications:
- Programming expertise
- Database proficiency
- Data modeling
- Data warehousing concepts
- Technical writing
- Formal technical education
- Business acumen
- Flexibility
Data Stewards vs. Data Analysts
The fundamental difference between data stewards and data analysts is that one oversees data, and the other engages with data. Data stewards make sure that data analysts have the highest quality information available.
Better data, both in terms of raw information and how it is organized, offers better insights from data analysts, and these insights can be provided more quickly.
Data stewards facilitate data analytics.
Data Stewardship Benefits
- Engages users from across the organization to collaborate to define data, build context around data, raise issues, and clarify roles and data owners
- Enhances data quality by simplifying processes, aligning users, and improving data quality to increase trust and confidence in data
- Supports faster and better data analytics with improved access and quality
- Provides mapping of data sources and storage locations
- Improves control of risks related to legal, privacy, and errors
- Enables data-driven decisions based on consistent, uniform data from across the organization
- Reduces costs in other areas of data management
Data Stewardship Programs
In practice, the success of data stewards hinges on the quality of data stewardship programs. A high-level process for evaluating an existing data stewardship program or creating a new one includes the following steps:
- Define goals and success metrics.
- Analyze current state and identify gaps.
- Create a roadmap for developing, implementing, and maintaining the data stewardship program (include key stakeholders and a budget).
- Secure buy-in from stakeholders.
- Develop a detailed plan for the program.
- Implement the program.
- Monitor, maintain, and measure the data stewardship program.
The data stewardship program should include these critical areas in its framework:
- Data architecture
Pay close attention to the structure of data and data-related resources. - Data integration and interoperability
Consider how the following data functions will be handled—acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization, and operational support. - Data modeling
Establish processes for the analysis, design, building, testing, and maintenance of data models. - Data quality
Put protocols in place to define, monitor, and maintain data integrity to help sustain data quality. - Data security
Be sure systems are in place to provide appropriate privacy, confidentiality, and access. - Data storage and operation O
Oversee data storage, use, and management. - Data warehousing and business intelligence (BI)
Manage data processing and enable access to data for analysis and reporting. - Master data
Manage shared data to reduce redundancy and enhance data quality with standardization rules. - Metadata
Provide guidelines for collecting, categorizing, maintaining, integrating, controlling, managing, and delivering metadata.
Common Data Stewardship Activities
Data steward programs provide structure for a number of data stewardship activities that fall into several broad categories.
Data quality
- Determine data-quality metrics and requirements.
- Define values, ranges, and parameters for data elements.
- Establish procedures for detection and remediation of data quality issues.
- Evaluate data quality to identify anomalies and discrepancies on an ongoing basis.
Policies and Procedures
- Define policies and procedures for data usage.
- Set criteria for data access.
- Evaluate data breaches or vulnerabilities—suspected and actual threats.
Privacy, Security, and Risk Management
- Manage data proliferation.
- Enforce privacy controls.
- Compile retention, archival, and disposal requirements.
- Create and implement data curation practices.
- Facilitate compliance with internal, industry, and government regulations.
- Establish and maintain a balance between data transparency and privacy.
Operational Oversight
- Oversee the lifecycle of data.
- Create and implement policies and procedures for the day-to-day operational and administrative management of systems and data (i.e., intake, storage, processing, and transmission of data to internal and external sources).
- Define and document data and its related terminology.
- Ensure that key data elements have clear definitions.
The Data Steward: A Digital Data Sheriff
Data stewards have a willingness to care for data assets that do not belong to them. They serve the organization as a vigilant protector of all data, representing the interests of the group at large—sometimes the entire organization or, in some cases, just for a group.
With an abiding interest in the overall health and wellness of an organization’s information assets, data stewards are critical to the success of data governance and resulting data intelligence.
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Last Updated: 2nd August, 2021
