Data Security Guides

Everything you need to know about how to keep your data secure and accessible.

An Introduction to Data Security Solutions

Data use is a must-have for modern organizations to compete. Without it, leaders in every industry risk falling behind on insights that can help drive informed decision making. But a proliferation of threats to data, and regulations dictating its use, add another must-have to the equation: data security. This is a look inside the rapidly evolving landscape of data security solutions.


What Are Data Security Solutions?

Data security solutions are designed to protect data from unauthorized access, use, and other risks. By aggregating a number of different functions, from data discovery to auditing, these platforms aim to break down silos, provide full coverage of and visibility into authorized data use, and streamline security operations.

The adoption of data security solutions is on the rise. According to Gartner, 75% of CISOs surveyed said they were actively trying to consolidate their data security vendors – a 46% jump from just two years earlier. As organizations aim to enable self-service analytics in increasingly complex data environments, it is safe to assume the movement toward streamlined data security solutions will continue.


What Are the Core Components of Data Security Solutions?

While specific capabilities will vary from platform to platform, organizations should prioritize this core set of features to achieve full data security coverage.

Data Discovery and Classification
Keeping tabs on what data you have in your possession can be a full-time job – and even then, at the rate that data volumes are growing, there’s a high likelihood of data slipping through the cracks. Sensitive data discovery capabilities remove the manual effort and associated risk from this process by dynamically scanning connected data sources for sensitive information and tagging it appropriately. Data classification is a closely related process that identifies the types of data an organization possesses and defines the processes for managing confidentiality.

Incorporating data discovery and classification into data security solutions not only removes the burden and risk of manual human inspection, but also streamlines the implementation of downstream data security processes and policies. This first line of defense helps organizations proactively protect data, and therefore is a critical feature of modern data security solutions.

Identity and Access Management
IT teams have been using identity and access management (IAM) systems to simplify access to organizational tools for years. However, there has long been a disconnect between IAM information and data access control. Why does the user data that can grant access to systems and platforms not extend to data sources and tables?

Failing to take advantage of the information within IAM platforms like Okta creates additional manual work for data platform teams, who must respond to individual data access requests. When employing multiple cloud platforms within a single data environment, this becomes even more complex. Data security solutions that integrate with IAM systems and can leverage their data in access control policies vastly reduce this complexity. Incorporating identity and access management across cloud platforms helps achieve broad scale data protection without additional overhead.

Data Access Control
Data access control is a central component of data security platforms because it is the oversight mechanism through which data teams govern who can access and use an organization’s data, both internally and externally. Without access controls, anyone may be able to discover and access data, regardless of how sensitive or regulated its contents are. This is a lose-lose scenario, with the data owners liable for penalties and legal action, and data subjects vulnerable to privacy violations.

Flexibility is key for data access control; overly restrictive policies may lock down data too tightly and limit its utility, while overly permissive policies expose data to risk and threaten the security of sensitive information. Data-driven organizations must strike the right balance between utility and privacy if they want to derive value from data and avoid potential financial, legal, and/or reputational repercussions.

Of the four main access control models – discretionary, mandatory, role-based, and attribute-based – attribute-based access control (ABAC) is best suited for modern data security solutions. By building policies based on user, environment, object, and action attributes, ABAC enables dynamic policy enforcement that requires minimal manual effort. As a result, data security solutions can run more efficiently and scale at the speed of an organization’s needs.

Data Masking and Encryption
Many of today’s regulations protecting data access and use require data to be modified in a way that hides or changes sensitive information. For example, data masking techniques like nulling and generalization keep users from seeing actual sensitive information, while preserving the utility of the data set as a whole. Creating a “fake” version of the data allows it to be usable for analytics without impacting the underlying information. Dynamic data masking is essential from a data security and compliance standpoint because it enables data sharing, which is a critical capability for modern organizations.

To cover the broad spectrum of data security and privacy needs, the best data security solutions will also offer privacy enhancing technologies (PETs). PETs comprise a range of advanced privacy controls, including differential privacy and randomized response, which bolster data masking capabilities and help de-identify sensitive data with mathematical guarantees.

Like masking, data encryption protects data by modifying its values. However, encryption secures data with an illegible code that can only be reversed using a corresponding encryption key. The technique is therefore commonly used for data in storage or transit. This makes data encryption a key function to consider when choosing data security solutions to protect against insider threats.

Data Monitoring and Auditing
Proactively tracking how data is being used can help detect anomalies before they become catastrophes. This starts with strong data monitoring and auditing capabilities that are integrated into data security solutions.

Data security solutions may integrate with security information and event management (SIEM) systems, and offer a native unified audit model. Both approaches aggregate activity from across platforms so data monitoring and auditing can be done holistically, helping to ensure no irregularities slip through the cracks. In addition to risk reduction, these approaches decrease the manual effort and time needed to sift through and correlate data activity and audit log information from different platforms.

Amid the rapid expansion of data rules and regulations, auditing is a fundamental capability for data security solutions. To maintain compliance, organizations that collect, store, and use data must keep audit logs and be able to provide proof that data use is fit for purpose. Without this accountability, data security will likely be deprioritized and consequently weakened.

Data Threat Detection and Response
One of the main goals of data security solutions is to identify and remediate potential threats to data before they can spiral out of control. However, the volume and speed of data use today can make detecting these threats like finding a needle in a haystack.

Data threat detection is made easier when access control policies are centralized within a data security solution and deployed universally. Maintaining a single source of truth for data security, governance, and platform teams to verify user access increases transparency and takes the guesswork out of anomalous data use. Coupled with data detection capabilities, such as activity views, behavior and risk analytics, real-time alerts, and anomaly reports, proactive responses can be much more streamlined and effective.

Federated Data Governance
As decentralized architectures like data mesh become more mainstream, maintaining consistent data access control implementation and avoiding data silos can be complex and prohibitive. With multiple stakeholders using and sharing data across lines of business, managing data access requests and monitoring use puts a heavy burden on data engineering teams. To support these architectures, data security solutions must be flexible, agile, and scalable. This starts with centralizing access control definitions, then putting governance back in the hands of data owners through a system of federated data governance.

Enabling distributed data stewardship gives data owners across lines of business the ability to build upon centralized, global access controls, so they can ensure policy enforcement is compatible with business context. Policies authored in plain language are easy for non-technical stakeholders to create, approve, and dynamically enforce, without the bottlenecks and complexity that come with manually managing one-off access requests across all domains. The flexibility and scalability this creates reinforces why data security solutions that enable federated data governance are best suited for modern and evolving data architectures.


How Do Data Security Solutions Work?

The right data security solution will be one that offers the core components mentioned above, and integrates seamlessly with your existing tech stack. Fundamentally, data security solutions should continuously discover sensitive data, secure it, and detect threats and anomalous use. An effective approach to data security is one where:

  • Data security solutions are connected to data sources, including cloud data platforms and IAM systems, so data assets and user metadata are automatically integrated
  • The solution scans new data sets as they enter the environment, identifies sensitive information, and tags and classifies it for future policy implementation
  • Data security, platform, and governance/legal teams work together to create, approve, and implement appropriate access control policies that are centralized within the data security platform but deployed across all connected data sources
  • User access is permitted or restricted at query time based on the access control policies and, in ABAC systems, a number of dynamic attributes
  • Continuous data monitoring works in the background to track data activity, deliver user behavior and risk analysis, and detect anomalies that trigger alerts
  • Audit reports can be run on-demand to prove compliance with relevant rules and regulations

Next Steps for Implementing Data Security Solutions

Once you know the core facets of data security solutions, you can make an informed decision about which tool is right for your organization’s data needs. With a holistic approach to discovering data, securing it, and proactively detecting threats, your entire tech stack will run more efficiently while you get the peace of mind that your data is protected.

Now that you know the basics of data security solutions, find out the top cloud data security best practices.