Data Governance is a critical aspect of modern data management practices. With the increasing volume of data and the rising scrutiny around data privacy, organizations must ensure they have effective data governance strategies in place. In this blog, we'll explore three ideas that can help simplify your approach to data governance, leading to reduced costs and mitigated risks of non-compliance.

One of the simplest ways to simplify your data governance approach is to minimize the number of data copies within your organization. In many enterprises today, data copies and replications have become the norm. This leads to multiple versions of the same data, making it challenging to manage a single version of truth and increasing the administrative burden. Additionally, having more data copies exposes organizations to greater cyber threats as each copy becomes a potential target for cybercriminals. By leveraging data virtualization technology and implementing a logical data fabric, you can significantly reduce the need for data copies. Instead of creating new data repositories for different use cases, virtual data views can be created on top of existing data sources. This not only reduces data duplication but also allows for the maintenance of a single authoritative data source. Furthermore, having fewer data copies simplifies compliance efforts, making it easier to execute tasks such as "right to be forgotten" requests required by regulations like GDPR.

In today's highly distributed data landscape, maintaining control over data access can be a daunting task. Different data repositories and technologies often have varying approaches to access control, making it challenging to ensure consistent and granular control over data access. This complexity is further amplified when changes in access control are required, involving multiple teams and systems. A logical data fabric layer, powered by data virtualization technology, can help centralize and simplify data access control and monitoring. By mapping all data sources into a logical data fabric layer, organizations can streamline the control of data access. This centralization enables a domain-specific approach to data access, allowing for granular control over data access and enforcement of global as well as local-level data access policies. Additionally, consolidating operational and active metadata within a single platform allows for better tracking and reporting of data usage and activities, especially regarding access to sensitive data.

Data security policies play a crucial role in data governance, defining rules and policies for data access and usage. Implementing and maintaining data security policies can be challenging, especially when dealing with complex data repositories and evolving compliance regulations. Traditionally, data security policies were implemented at the database level, leading to maintenance issues, SQL skills requirements, and an explosion of multiple views across multiple systems. To simplify the implementation of data security policies, consider decoupling them from the underlying data repositories. Data management platforms offer a technology-agnostic approach to global data security policy implementation. By defining the necessary business rules at the logical data layer, these policies can be applied consistently across all data repositories and BI tools. This approach allows for easy addition of new data sources, users, and BI tools, reducing ongoing effort and providing scalability. Additionally, linking data policies to semantic objects (tags) provides even more flexibility and simplification, enabling organizations to maintain and update policies centrally.
 

As data management and architecture become increasingly complex, organizations must simplify their approach to data governance. By minimizing data copies, centralizing data access control and monitoring, and decoupling data security policies, organizations can significantly simplify their data governance practices. Leveraging data virtualization technology, these ideas can be implemented effectively, regardless of the industry or business function. Simplifying data governance not only reduces costs but also helps mitigate the risks associated with non-compliance, ensuring organizations can effectively manage and protect their data in today's data-driven world.