Effectively managing data is now a key factor in business success. Whether you’re a small startup or a multinational corporation, the quality and accessibility of your data can make all the difference. It helps businesses make informed decisions, discover new opportunities, and stay ahead of the competition. Data enablement and data governance are two methods organizations use to secure and use their data.
This article provides a detailed comparison between data enablement and data governance by covering the following topics:
What is Data Governance?
Data governance is a crucial aspect of effective data management. It involves the development of policies, processes, and standards that ensure data accuracy, security, and compliance. Maintaining data accuracy, security, and compliance allows organizations to fully utilize their data assets to support decision-making. Typically, data governance principles include elements of data quality, data security, data privacy, and data lifecycle management.
Effective data governance frameworks rely on clear policies and procedures for data management. When successful, a data governance framework reduces the risk of data breaches, avoids penalties for non-compliance, and improves the accuracy and reliability of data assets.
What is Data Enablement?
Data enablement provides employees with the necessary tools, technologies, and processes to access and analyze data easily and efficiently. It enables employees to make data-driven decisions and drive successful business outcomes. A data enablement approach encourages data democratization, empowering employees to access the data they need to drive their work and make informed decisions.
Organizations must provide employees with easy access to relevant data, regardless of its source or format to achieve data enablement. Employees also require the tools and technologies to work with data based on their roles. This includes self-service analytics tools, data discovery platforms, and data visualization tools that enable employees to analyze and interpret data without relying on IT or data science teams.
Implementing data enablement improves collaboration, decision-making, and innovation by giving employees the data they need for success. This helps create an organizational culture focused on leveraging data to inform all aspects of work.
Data Enablement vs. Data Governance
Data enablement and data governance are two approaches to data management that are often pitted against each other. However, these approaches are not necessarily mutually exclusive, and combining the two can lead to more effective data management. Effectively combining the two requires a detailed understanding of their differences and similarities.
Read more about Why Cloud Data Governance is Difficult and Agile Data Governance with Satori
What Makes Data Enablement Unique?
Data enablement is focused on making data more accessible to users across an organization. This approach involves removing barriers that hinder users from accessing the data they need, such as complex data structures, lack of data integration, and limited access to data sources. The goal of data enablement is to enable users to make better decisions by providing them with the data they need, when they need it.
Data enablement often involves a decentralized approach, where different teams and departments can manage the use of their own data assets. However, it still incorporates a centralized data enablement platform to unify data across an organization. A decentralized approach gives teams more control over their data making it easier to customize the data assets to their needs.
What Makes Data Governance Unique?
Data governance is a structured approach to managing data that involves defining policies, procedures, and guidelines for data management. The primary goal of data governance is to ensure that data is accurate, reliable, and secure, as well as in compliance with relevant regulations and standards. It typically involves a centralized team responsible for establishing and enforcing these policies and procedures across the organization.
A data governance team usually includes data stewards, data owners, and other data management professionals. They establish and maintain data standards, policies, and procedures, as well as monitor compliance with regulations and standards. Data governance also involves managing metadata, data quality, and data lineage.
Combining Data Enablement and Data Governance
A combination of data enablement and data governance ensures that data is not only easily accessible but also accurate, reliable, compliant, and secure. Here are three steps organizations can take to effectively combine these two approaches:
- Establish a clear data strategy: A clear data strategy is crucial for effective data management. It should define your organization’s goals and objectives for data management, as well as the roles and responsibilities of those involved. A clear data strategy outlines the roles of data governance and data enablement to align with business objectives.
- Include data enablement in your data governance framework: By incorporating data enablement policies and procedures into your data governance framework, you can ensure that data is not only accurate, reliable, and secure but also easily accessible to those who need it. This can help improve decision-making across the organization.
- Use tools that combine data enablement and data governance: Tools that combine data enablement and governance can help organizations streamline their data management processes and ensure that data is both accessible and secure.
Common Misconceptions of Data Enablement and Data Governance
Despite the benefits of both data governance and data enablement, there are some common misconceptions that can prevent organizations from effectively implementing these approaches.
One common misconception is that data governance is too rigid and inflexible, and can hinder innovation and creativity. However, effective data governance is designed to be adaptable and flexible, and can actually support innovation by ensuring that data is accurate and reliable.
Another misconception is that data enablement is a free-for-all approach that can lead to data chaos and security risks. But, data enablement actually establishes clhear guidelines and standards for data access and use. It also ensures users receive proper training in data management best practices.
Conclusion
Data governance and data enablement are two approaches to data management that serve different purposes but can work together to improve data management practices. Data governance establishes policies and procedures for data management, ensuring accuracy, reliability, and security, while data enablement focuses on providing easy access to data for users. By combining these approaches, organizations can improve data quality, facilitate data access, and ensure compliance with regulations.
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