It’s no secret that the need for organizations to be “data-driven” is more critical than ever in today’s fast-paced business environment. Having effective data analytics processes can help enhance a company’s operations, processes, and decisions, as well as the customer experience, boosting its overall competitive advantage.
Still, despite the drive to be more data-driven, organizations are struggling to meet this goal. In fact, recent data shows that only 26.5 percent of businesses report having established themselves as a data-driven company. Why? Many IT teams are facing challenges around juggling security and compliance while remaining competitive with their data use.
Another recent study found that over half of data practitioners cite securing data with appropriate access rights as one of their biggest hurdles when it comes to their data-driven initiatives. This comes at a time when data privacy regulations are growing increasingly numerous and complex, and cyber security threats abound. As a result, organizations must find a way to secure their sensitive data without completely locking it down, so that they can continue to effectively leverage it for business purposes.
This is no easy task, but there are steps businesses can take to protect their sensitive data while allowing for trusted access. These include:
Using data classification to define access controls
Data teams traditionally define data access control based on the data itself, applying rules table-by-table or at the schema level. This approach is problematic for two reasons. First, it is unscalable. Second, it leaves room for ambiguity around who is actually qualified to define those rules. Therefore, instead of defining access controls based on the data, teams should leverage data classification, which is the process of identifying the types of data and then applying metadata tags or attributes accordingly. This creates an enhanced model that can scale with your data while also complying with regulations.
Consistently administering data privacy controls across all cloud data platforms and consumption approaches
While it’s critical to ensure that data privacy methods used to protect, control, and manage sensitive data access remain compliant with regulations, it’s equally important that they be consistently administered regardless of platform or consumption approach. This helps organizations avoid leaks or breaches from users with varying permissions accessing data across different platforms in your (multi-) cloud strategy.
Reinforcing data-sharing processes
Data sharing is essential in today’s business environment. However, keeping every single data exchange secure becomes increasingly challenging as data volumes grow and more data is shared internally and externally. Thus, organizations must take the necessary steps to ensure their data-sharing processes are adequately reinforced to avoid any data loss or breaches. For instance, teams can augment centrally imposed rules for regulatory compliance with rules defined by data owners for business and contractual compliance. Or they can leverage federated models for access control management to share data in a secure manner.
Ensuring constant visibility into sensitive data management for regulatory compliance
In order to meet evolving regulations for sensitive data and remain compliant, organizations must maintain continuous visibility into their data activities, including the type of data, where it is being accessed, and specific requirements or rules that apply to it. This requires seamless collaboration between legal teams (from a regulatory perspective) and the data platform team (on the data management side).
Scaling data access controls according to business needs
While effectively controlling who can access sensitive data becomes more difficult as data volumes increase, these policies and controls must also scale as the organization grows and evolves. With every new hire and role change, an employee’s data access privileges must be updated accordingly, or else they bring the same access rights to their new role or team. Alternatively, data teams can leverage attributes, which automatically give users appropriate access to the data based on their business needs as they move through the organization. To remain agile, secure, and compliant, companies must scale their access controls proportionately to their expanding data demands.
Establishing an ironclad data security strategy
At the end of the day, organizations need a strong and long-lasting data security strategy that can hold up against increasing security threats and remain effective in growing cloud data environments. Maintaining this strategy across all architectures remains key to avoiding non-compliance and unauthorized access. To accomplish this, IT teams should look to incorporate a combination of the following into their strategies: encryption, data masking, identity access management, authentication, data backup and resilience, and data erasure.
Striking a balance between data security and access is easier said than done, and every organization’s approach will look slightly different depending on its unique business needs. However, it is critical for businesses to begin establishing a powerful, resilient, and scalable data security strategy now, as regulations continue to become more stringent and security threats more complex. Following these key steps is a good place to start.
