In today’s data-driven landscape where data is power, organizations remain hyper-focused on how to leverage their data for BI, analytics and other business-driving initiatives. In fact, recent research shows that data leaders are primarily motivated by the need for high-quality analytics insights over compliance.
However, in response to increasingly complex data privacy regulations and cybersecurity threats, organizations have no choice but to reexamine their data policies and rein in how data is accessed, processed, analyzed and shared. Most recently, the focus of privacy regulations has veered towards safeguarding personal data specifically, forcing teams to shift their data frameworks to remain compliant and secure.
This has created a “crossroads” in the data security conversation around how to best juggle security and compliance, while remaining competitive with data. To have their cake and eat it too, teams must take the right steps to protect their sensitive data without completely locking it down, so they can continue to harness the power of data to propel their business forward.
It’s a tricky balancing act, but there are a few best practices data teams can follow to help effectively secure their sensitive data while enabling trusted access. Here are six tips for organizations to help achieve data security success in our current technology environment.
Define access controls based on data classification, not the data itself
Traditionally, data access control is defined based on the data itself, and data engineers or database administrators apply rules on a table-by-table basis. Not only is this unscalable, but you can also question if they are the right people to define those rules. A better approach is to use data classification, which is the process of identifying the types of data your organization holds and applying metadata tags or attributes, as the basis for data access controls. Then, to keep up with increasingly complicated regulations like Schrems II and GDPR, another best practice is to involve the legal or compliance teams in defining access controls. By defining access controls based on data classification and engaging the right people, you create a model that can scale with your data while complying with regulations.
Enforce data privacy controls across all data platforms and consumption approaches
Data privacy methods that organizations implement to protect, control and manage sensitive data access are highly regulated. And while it’s important to always ensure that these controls remain compliant and legal, it’s also key that they are consistently administered across all consumption approaches and platforms. Ultimately, data access should be consistent, regardless of the platform. This is the best way to prevent potential leaks that can occur when users with varying permissions access data across different data platforms.
Reinforce data sharing processes
Despite growing data security concerns, it is clear that data sharing is essential in today’s business landscape. As data volumes continue to grow and organizations increasingly share more data both internally and externally, teams face the challenge of keeping every single one of these exchanges secure. This is especially vital if businesses are striving to obey specific data use and licensing agreements that enable them to monetize their data products. As a result, organizations should ensure their data sharing processes are adequately reinforced to avoid any data loss or breaches. Federated models for access control management help teams to share data in a controlled way. Centrally imposed rules for regulatory compliance can be augmented with rules defined by data owners for business and contractual compliance.
Maintain visibility into sensitive data management for regulatory compliance
To meet mandatory regulations and compliance laws for sensitive data, organizations need to have constant visibility into what type of data is in their possession, where it is being accessed and the specific rules or requirements that apply to it. Having this information is especially helpful as regulations evolve or are created. For optimal visibility into their organization’s sensitive data management practices, this requires legal teams to coordinate with the data platform team, which handles the data and applies the policies, and the business team that authors them. This visibility not only helps prove compliance with regulatory requirements, but it also makes it easier to change access controls when required.
Scale data access controls with organization needs
Controlling who can access sensitive data becomes more complex as data volumes, users, technologies, and regulations continue to grow and evolve, especially when trying to enforce policies consistently across platforms and access requests. It is not only the data that evolves but the organization as well. New people will join, employees will get promotions, and others might change teams internally. HR departments typically have JLM (joiners, leavers, movers) processes in place, but data platforms should also have such safeguards. Why? Once a user is approved in a manual access request, they will have access to the data no matter what other teams they may join in the future. However, by leveraging attributes, you can automatically give users access to the data they need when they join and as they move through the organization. To adapt and evolve, organizations must work to scale their access controls proportionately to their expanding data needs so that all of their security and access demands are sufficiently and efficiently met.
Implement a strong and lasting data security strategy
Finally, in order to effectively secure sensitive data, organizations need a comprehensive and ironclad data security strategy that combats security threats in increasingly decentralized cloud data environments like data lakehouses and data mesh. Again, security must be maintained across all architectures to prevent unauthorized access or non-compliance. Strategies can look very different from business to business, but most commonly involve some combination of encryption, data masking, identity access management, authentication, data backup and resilience and data erasure.
At the end of the day, there’s no silver bullet for guaranteed data security and access success. Every organization’s approach will look slightly different and continue to evolve depending on its data and security needs of the day. However, these fundamental best practices are a good place to start and are key to establishing a powerful, resilient and scalable data security strategy for years to come.