In today’s data-driven world, the democratization of data has become crucial to ensure the competitiveness of companies. According to a report, data-driven companies generate 70% more revenue per employee than their counterparts. However, democratizing data can pose a significant risk to data governance and privacy, potentially leading to data loss, a breach and other undesirable consequences. Therefore, it is essential for Chief Information Officers (CIOs) to take a proactive approach and implement measures to ensure that data democratization does not affect governance.
Here are four keys that can help CIOs democratize data without compromising governance:
Base access on roles:
In order to achieve data democratization without compromising governance, CIOs should prioritize establishing a robust system of role-based access controls (RBAC).
Data democratization means that employees can access data more easily, streamlining processes and improving productivity. However, not all data should be visible to everyone. To address this, companies can use a data virtualization platform to configure role-based access controls (RBAC) at a central layer, allowing them to specify which roles can access which data. This ensures that employees can only access data that corresponds to their role and level, minimizing the risk of data breaches.
To begin implementing RBAC, it is crucial to collaborate with other stakeholders in the organization such as HR or legal teams. This can help ensure that roles are accurately defined and appropriately assigned. It is also important to periodically review and update roles as the organization evolves and new data sources are added.
Once roles have been established, enforcing RBAC consistently across the organization is essential. This requires a strong governance framework that includes regular monitoring and auditing of access controls, as well as training and awareness programs to ensure that employees understand the significance of data security and privacy.
Control the use of data:
Controlling access to data is undoubtedly crucial; however, comprehending the intended purpose of data is equally important. Organizations have an obligation to manage and utilize their data appropriately, and it is essential to monitor who is using or altering which data, and how and when it is being accessed. Ensuring that employees use data for its intended purpose is critical to maintaining compliance with industry regulations and safeguarding the organization’s reputation.
Data virtualization platforms can play a crucial role in controlling the use of data. By recommending data sets that best suit users’ purposes, these platforms can help employees find the right data for their needs while also ensuring that they are using it appropriately. The semantic layer in data virtualization provides a standardized way of naming and organizing data, ensuring that all records follow a common taxonomy. This helps to prevent confusion and chaos, which can arise when employees are working with multiple sources of data that are not consistently named or organized.
To implement effective control over the use of data, CIOs need to ensure that their data virtualization platform is configured correctly. This involves setting up policies and procedures for data use and ensuring that they are enforced consistently across the organization. It also requires regular monitoring and auditing of data used to identify any potential misuse or unauthorized access.
Secure backend systems:
Allowing all employees to use company data can lead to an overload of backend systems, such as Enterprise Resource Planning (ERP) systems. Virtualization can help define specific constraints for queries, such as limiting the number of queries that can be performed simultaneously, setting a time limit before auto-termination, or restricting the number of rows in the result. By doing so, virtualization ensures that backend systems are not overloaded and that data remains secure.
Furthermore, it is imperative to ensure that backend systems are fortified with robust access controls, data encryption, and regular system updates. These measures serve to preclude unauthorized access and maintain the security and confidentiality of data against potential security threats.
In addition to securing backend systems, it is also indispensable to establish and implement adequate disaster recovery and business continuity plans. Such plans can help mitigate the impact of any unforeseen disasters or disruptions, thereby ensuring that data remains secure and business operations continue uninterrupted.
By taking a comprehensive approach to secure backend systems, CIOs can achieve data democratization without compromising governance or security. This approach provides the necessary controls to safeguard data while enabling employees to access and utilize data more effectively and efficiently. It is essential to prioritize the security of backend systems and maintain a proactive approach to addressing potential threats and vulnerabilities to preserve the confidentiality, integrity, and availability of organizational data.
Filter data queries:
Data democratization implies that many employees may carry out queries without technical knowledge, which can lead to data loss or system overload. Therefore, it is essential to restrict the areas that employees can access to prevent them from accessing the entire company database. A filtering system can be an effective solution to grant access to data without having to worry about system overload and skyrocketing costs.
Before making any decisions based on filter data queries, you should test and validate your analysis. This can involve running sensitivity analyses, comparing results to other data sources, and reviewing assumptions. It is important to document your process when using filter data queries. This includes documenting your objectives, data sources, filters, and any assumptions or decisions you make. This will help to ensure that your analysis is transparent and repeatable.
When utilizing filter data queries, it is advisable to commence with a limited set of data and then progressively increase the scope as you gain familiarity with the methodology. This will help you to identify any issues or challenges early on and adjust your approach as necessary. RBAC, ABAC, and Data Masking are some of the most effective filtering methods that organizations can use to control access to data and ensure that data democratization is done while maintaining governance.
Conclusion
CIOs must ensure that data democratization does not affect governance, as it can pose significant risks to the company’s privacy and data. By implementing the four keys outlined above, CIOs can ensure that data democratization is done in a controlled and secure manner, improving productivity while minimizing the risk of data loss.
