5 Reasons Why Data Governance is Critical for Data Democratization
- By Intelliswift
- 18 April, 2023
-
-
A recent Gartner CDO report states that data & analytics teams who successfully increased data sharing demonstrated verifiable value 1.7 times more effectively to stakeholders. In recent years, there has been a growing emphasis on data democratization - the practice of making data accessible and usable by everyone in an organization. This shift towards democratizing data is driven by the realization that data is a valuable asset that can be used to gain insights, make informed decisions, and drive business outcomes.
However, as organizations move their data to the cloud, it is essential to ensure that appropriate data governance policies and practices are in place to maintain data quality, security, and compliance. Additionally, as AI technologies become more prevalent, establishing robust data governance ensures that AI models are accurate, ethical, and compliant with regulatory requirements.
In this blog post, let's examine why data governance in the cloud era is essential for democratization and business agility.
- Maintaining data quality: Data democratization means that more people will have access to data. Unfortunately, this increased access can lead to duplication or inaccuracy. Data governance can help ensure consistency and accuracy by establishing standards for data quality. Policies can include data validation processes, data cleaning, and data auditing. By enforcing these policies, data quality can be maintained irrespective of the number of people that access the data.
- Ensuring data security: Data democratization can also present significant risks around data security. Wider access to data increases the risk of data breaches and misuse. Data governance helps to mitigate these risks by establishing security policies and access controls. These policies can include encrypting sensitive data, ensuring access to only authorized personnel, authentication protocols and regularly backing up data.
- Complying with regulations: Data democratization can create significant risks around compliance with regulations. Laws such as General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) require companies to ensure that personal data is protected and managed appropriately. With well-established data governance policies, organizations can reduce the risks of breaches, demonstrate compliance, and provide complete privacy and security.
- Promoting data sharing: Data democratization fosters collaboration and data sharing across departments. However, collaboration can also lead to data silos, where departments store their data independently, leading to duplication of effort and inconsistency in data. With data governance, businesses can help prevent data silos by establishing standards for data sharing and collaboration. By adopting the right policies and procedures for data sharing, departments can work together more effectively, and data can be managed more efficiently.
- Driving business agility: Data governance policies and practices help to drive business agility by enabling organizations to quickly and easily access and use data to make informed decisions. This agility is critical in today's fast-paced business environment, where organizations must be able to respond quickly to changing market conditions and customer needs.
Best Practices for Data Governance
Data democratization is a crucial step towards creating a data-driven culture and enabling informed decision-making across departments. However, it is not about providing everyone access to data. Organizations need to identify the types of data that can be shared and the right people that it can be shared with, establish data access controls, and encourage data-sharing agreements that outline the terms and conditions for data use. Additionally, organizations should have processes in place for monitoring and auditing data-sharing activities to detect any misuse or unauthorized access.
Data governance can help in providing a framework to manage data assets throughout their lifecycle, from acquisition to disposal.
- Establish a data governance framework: A strong data governance framework is essential for data democratization. It provides clear guidelines for data access, data use, and data sharing, ensuring that data is accurate, secure, and compliant with regulations. A data governance framework should include policies and procedures for data management, data security, and data privacy.
- Provide self-service analytics tools: Self-service analytics tools empower employees to access and analyze data without relying on IT or data science teams. These tools should be intuitive and user-friendly, allowing employees to easily create reports, dashboards, and visualizations to gain insights into business operations.
- Develop a data literacy program: Data literacy is the ability to read, interpret, and communicate data effectively. Developing a data literacy program helps to ensure that employees have the skills and knowledge needed to understand and use data properly. This program should include training on data analysis, data visualization, and data storytelling.
- Foster a culture of collaboration: Collaboration is essential for data democratization. Employees from different departments and functions should work together to identify data sources, share insights, and drive business outcomes. This culture of collaboration can be fostered through cross-functional teams, data-driven decision-making, and open communication channels.
- Emphasize data security and privacy: Data security and privacy are critical for data democratization. Organizations need to implement strong security controls such as encryption, access controls, data backup and recovery procedures. They should also comply with regulations such as GDPR, HIPAA, and CCPA, to ensure that data is protected and privacy is maintained. It is also essential to educate employees about compliance and how they can enable adherence.
- Measure success: To ensure that data democratization is driving business agility, organizations should measure their success using key performance indicators (KPIs). KPIs could include metrics such as the number of users accessing data, the frequency of data usage, and the business outcomes achieved through data-driven decision-making.
Conclusion
Data democratization is a powerful way to unlock the full potential of data in any organization. However, it requires a comprehensive approach to data governance to ensure that data remains accurate, secure, and compliant. By establishing clear data governance policies and making sure that they are followed, organizations can ensure that data is accessible to everyone in the organization while maintaining high standards of data quality, security, and compliance. This can lead to more informed decision-making, improved collaboration, and a data-driven culture that drives innovation and growth. The benefits of data democratization are clear, but it is crucial to implement with a thoughtful and strategic approach to ensure that it is successful and sustainable in the long term.
Intelliswift's robust data management and analytics practice helps several organizations understand data sovereignty and compliance. Connect with us to learn how you can maximize data effectiveness for shaping business decisions.
