An Introductory Guide to Data Stewardship

What Is Data Stewardship?

It's important to understand the distinction between data governance and data stewardship, as both terms are often used interchangeably but have different meanings.

Data governance refers to a broader organizational framework that defines policies, processes, and standards for managing data assets. It ensures that data is used in an effective, consistent, and secure manner throughout the entire organization. 

Data stewardship is an aspect of data governance. It focuses on the day-to-day activities and responsibilities of individuals or teams tasked with developing and sustaining data governance practices. Data stewardship ensures that users across the organization have access to the data they need. It spans the entire data life cycle, from collection to transformation, use, storage, archiving, and deletion. 

In essence, data governance offers a broad framework, whereas data stewardship is the practical application and enforcement of that framework. 

Who Is a Data Steward?

A data steward is a significant member of an organization who's in charge of protecting and optimizing the company's data assets. They carry out an important role in ensuring that data is gathered, kept, used, and safeguarded in compliance with data governance policies.   

Data stewards are responsible for guaranteeing data accuracy, consistency, and reliability, as well as securing it from unwanted access and misuse. 

Roles of a Data Steward

A data steward's role includes various tasks to ensure the quality, integrity, and security of an organization's data. Here are the main roles: 

• Data life cycle management: Data stewards manage the full data life cycle, from creation and storage to archiving and deletion. They guarantee that data is managed correctly at all stages following regulatory and organizational requirements.
• Data ownership and governance: The steward identifies who is responsible for specific datasets within the organization, creates and enforces data management rules and standards, and ensures compliance with established data governance principles.
• Data quality: They check the accuracy and completeness of data and guarantee consistency across systems and sources. Also, they detect and fix data quality issues.
• Data security: Data stewards protect sensitive data from unauthorized access and prevent data breaches by applying security measures that ensure data accuracy and reliability.
• Training and awareness: Data stewards often help other employees with training and resources to promote best practices in data management. They increase awareness about the significance of data governance and quality, fostering a culture of responsible data use.

Skills and Competencies of a Data Steward

A data steward has many technical, analytical, and interpersonal skills and competencies. Here's the breakdown: 

Technical Skills

• Data management and governance: Data stewards must thoroughly understand data management principles such as data governance frameworks, data quality management, and metadata management. They should be conversant with tools and software used in data governance, such as data catalogs, data quality tools, and database management systems.
• Data security and compliance: Understanding data security policies and regulatory requirements is important. Data stewards need to understand data protection rules (such as GDPR and HIPAA) and be able to implement security measures to protect sensitive information.
• Database and SQL proficiency: Understanding database management and SQL is vital for querying, updating, and managing data in relational databases. This competence allows data stewards to effectively work with datasets while ensuring their integrity.

Analytical Skills

• Problem-solving: Analytical thinking is essential for discovering the underlying causes of data problems and providing effective solutions. Data stewards must be creative in diagnosing issues and ensuring that corrective actions are fast and effective.
• Attention to detail: When handling data, a thorough approach is vital, as even minor errors can cause major issues. Data stewards must pay special attention to detail to ensure that their data is accurate and complete.
• Data interpretation and reporting: Data stewards must be able to evaluate complex data and create reports that give stakeholders valuable insights. This includes the ability to evaluate data patterns, monitor data quality indicators, and convey findings effectively.

Interpersonal and Communication Skills

• Collaboration and teamwork: Data stewards often work together with multiple teams and stakeholders, including IT, compliance, and business sectors. Effective communication and teamwork are necessary for ensuring that data governance principles are consistently followed and data is used efficiently.
• Communication and training: The ability to convey complicated data concepts in a simple and intelligible manner is important. Data stewards must communicate data governance policies, quality challenges, and best practices to both technical and non-technical audiences. They may also be in charge of training personnel in data management practices.
• Negotiation and conflict resolution: Data stewards may have conflicting interests when managing data. Strong negotiation and conflict resolution abilities are necessary to navigate these circumstances and develop solutions that are consistent with company goals.

Importance of Data Stewardship

As the amount and complexity of data increase exponentially, organizations face new challenges in managing and securing their data assets. Without adequate management and control, data can become fragmented, inconsistent, and unreliable, posing substantial risks and inefficiencies. 

Data stewardship is an important answer to these concerns. By providing explicit guidelines, roles, and responsibilities, a data steward ensures that data is collected, stored, used, and safeguarded following business goals and ethical standards. Here are some of the essential benefits that can be achieved from data stewardship. 

Higher-Quality Data

Data stewardship ensures excellent data quality, which is required for accurate decision-making. Stewards monitor and manage data, making sure that it's reliable, consistent, and error-free, allowing the company to make informed decisions based on trustworthy information. 

Improved Data Security and Compliance

Data stewardship enables firms to comply with data protection rules and regulations such as GDPR, HIPAA, and CCPA. Data stewards adopt security measures to secure sensitive information and ensure that data management processes comply with legal and regulatory standards. This decreases the likelihood of data breaches and the resulting penalties. 

More Informed Decision-making

High-quality, well-managed data leads to better decisions. Data stewards ensure that decision-makers have access to correct and up-to-date data, allowing them to make informed choices that propel the business forward. This is particularly important in data-driven businesses, where insights from data can provide a competitive advantage. 

Better Customer Experience

High-quality data may be used to personalize customer experiences, which increases customer satisfaction and loyalty. Accurate and easily accessible data can also help improve customer service efficiency and responsiveness. 

Promoting Continuous Improvement

Data stewardship entails the continuous monitoring and refining of data operations. Organizations that consistently improve data quality and management processes may adapt to changing technology and business needs, ensuring that their data remains a useful resource throughout time.

Tools and Technologies for Data Stewardship

The key tools used in data stewardship are data management software, data quality tools, and collaboration tools. Here are some of the top examples in each category. 

Data Management Software

Examples of data management software include the following: 

• Oracle Database is a powerful relational database management system (RDBMS) that's widely used by organizations to store and manage structured data. Oracle's extensive features—including data protection, recovery, and high-performance analytics—make it a popular choice for enterprise data management.
• Microsoft SQL Server is an RDBMS that stores and retrieves data as requested by applications. SQL Server provides tools for data governance, security, and quality assurance, allowing you to manage complex databases efficiently.
• PostgreSQL is an open-source RDBMS known for its versatility and standard compliance. PostgreSQL provides tools for working with structured and unstructured data, as well as built-in integrity mechanisms to ensure data quality.

Data Quality Tools

Data quality tools help to ensure that data is accurate, consistent, and complete by finding and resolving errors. 

• Acceldata is a complete platform for data observability that is designed to assist organizations in maintaining the functionality, quality, and overall health of their data systems. It offers real-time insights and guarantees the accuracy and dependability of data at scale.
• Talend is a platform that helps data stewards clean, validate, and transform data by providing capabilities for data integration, data quality, and data governance.
• Trillium Software is a data quality platform that provides data profiling, cleansing, and enrichment capabilities to help data stewards identify and resolve quality concerns.
• IBM InfoSphere Information Analyzer is a tool for evaluating data quality and integrity by profiling it and ensuring it meets organizational standards.

Collaboration Tools

Collaboration solutions are vital for improving communication among data stewards, stakeholders, and users. 

• Confluence is a collaborative tool that allows data stewards to document policies, standards, and guidelines and share them with teams.
• ‍Slack and Microsoft Teams are communication platforms that allow data stewards to engage with other departments while delivering updates on data quality issues, governance standards, and access requests.

This post was written by Vincent Chosen. Vincent is a web developer and technical writer. He has proficient knowledge in JavaScript, ReactJS, NextJS, React Native, Nodejs and Database. Aside from coding, Vincent loves playing chess and discussing tech related topics with other developers.