An Introduction to Data Security Solutions
With 95% of businesses leveraging data for decision-making, there’s no question that data isn’t just a nice-to-have tool – it’s a must-have to compete in today’s market.
But managing data access is far from straightforward. As data volumes, users, regulations, and threats proliferate, 33% of data professionals say that a lack of visibility into data sharing and usage is their biggest security challenge.
As the complexity of modern data stacks grows, legacy approaches to data security no longer cut it. So, what should you look for in a data security solution built for the era of AI, data marketplaces, and advanced analytics? Here’s 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 – they 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. The 2024 State of Data Security Report found that 77% of respondents’ data security budgets increased within the past year, and 88% believe data security will become an even higher priority in the coming year. As organizations aim to enable self-service analytics in increasingly complex data environments, it is safe to assume that data security solutions will continue to be fundamental components of the modern data stack.
What Are the Core Components of Data Security Solutions?
While specific capabilities will vary from platform to platform, you should prioritize this core set of features to achieve full data security coverage.
Data Discovery and Classification
Manually 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. Automating sensitive data discovery removes the manual effort – and its associated risks – 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 your 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 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 is often a disconnect between IAM information and data access control. Why does the user data that grants 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. With multiple cloud platforms in a single data environment, this becomes even more complex. Data security solutions that integrate with IAM systems and 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 you govern who has access to your 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 it is. This is a lose-lose scenario, with 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 it to risk and threaten the security of sensitive information. To get value from your data and avoid risks – financial, legal, reputational, or otherwise – you must strike the right balance between utility and privacy.
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 dynamically enforces policy – with minimal manual effort. As a result, data security solutions run more efficiently and scale with your organization’s needs.
Data Masking and Encryption
Many of today’s compliance laws and regulations require you to modify data in a way that hides or changes sensitive information. For example, major laws like the GDPR and HIPAA explicitly call for data masking techniques like nulling and generalization, which obscure sensitive data for sharing and analysis. In the case of substitution or pseudonymization, a “fake” version of the data makes it usable without impacting the underlying information.
When evaluating data security solutions, dynamic data masking is essential for data security and compliance because it enables data sharing. According to a Gartner survey of chief data officers, organizations that focused on data sharing were 1.7x more effective in data and analytics functions than those that did not prioritize it.
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. When choosing a data security solution, consider data encryption to help with insider risk management.
Data Monitoring and Auditing
Proactively tracking how data is being used helps detect anomalies before they become catastrophes. This starts with strong data monitoring and auditing capabilities that are built into data security solutions.
Some data security solutions integrate with security information and event management (SIEM) systems, and offer a native unified audit model. These approaches aggregate activity from across platforms for holistic data monitoring and auditing. This helps ensure no unusual activity slips through the cracks, while reducing 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. When you collect, store, and use data, it’s imperative to keep data audit trails in order to prove that data use is fit for purpose. Without this accountability, you may be caught off guard by audit requests or unseen threats.
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 makes detecting these threats like finding a needle in a haystack.
Centralized data access management and policy enforcement make data threat detection substantially easier. Maintaining a single source of truth for 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, user behavior analytics, real-time alerts, and anomaly reports, proactive responses are 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 is often complex and prohibitive. With multiple stakeholders 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.
Distributing stewardship across data domains gives data owners the ability to build upon centralized, global access controls, ensuring 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 proactively detect threats.
An effective approach to data security is one where:
- Data security solutions connect data sources, including cloud data platforms and IAM systems, for automatic integration of data assets and user metadata.
- 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.
- Access control policies permit or restrict user access based on a combination 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.
- On-demand audit reports allow you to easily prove compliance with relevant rules and regulations.
Next Steps for Implementing Data Security Solutions
Knowing the core facets of data security solutions empowers you to 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.
To read more about securing data across your ecosystem, check out our guide to cloud data security best practices.