What is a data risk assessment?
A data risk assessment is a full evaluation of the risks that an organization’s data poses. The process involves identifying, classifying, and triaging threats, vulnerabilities, and risks associated with all your data.
In the cloud, this includes all data across PaaS and hosted databases, storage buckets, data warehouses, serverless resources, and development environments.
Why are data risk assessments important?
Simply put, data risk assessments are crucial. Businesses are managing, storing, and generating more data than ever before, and the adoption of multicloud strategies means that sensitive enterprise data is spread out.
Unlike general data risk assessments, a cloud data risk assessment pinpoints cloud-native risks and security challenges. As data proliferates and cloud environments get more complex, new data visibility, management, security, and compliance challenges crop up. Data risk assessments boil down these factors into a simple question: “What risks does my data pose?”
Let’s take a look at some important reasons why data risk assessments should be a top priority for businesses.
Cloud security: Cloud data security assessments help protect enterprise cloud environments, which are susceptible to internal risks like misconfigurations and vulnerabilities and external risks like cyberattacks. According to IBM, 80% of data breaches in 2024 involved some amount of cloud-based data. Thorough data security assessments are the best way to prevent data-related incidents and attacks (and they also streamline data management!).
Regulatory compliance: Data risk assessments can help you spot regulatory risks in data so that you stay compliant with laws and frameworks like GDPR, HIPAA, PCI DSS, and CCPA. Another benefit? Now that businesses increasingly port and store data in different countries, data risk assessments can also help address data sovereignty and compliance risks.
AI data security: Data risk assessments must also consider AI training data due to the unique security challenges it presents. AI models are only as good as the data they're trained on, and this data can be a significant source of vulnerability.
Cloud detection and response (CDR): The benefits of data risk assessments are wide and varied. For example, data risk assessments can help improve your CDR capabilities. Here’s how and why: By knowing where crown jewel data is and what risks it holds, you can detect and remediate the most pressing threats first and keep them from maturing into large-scale incidents.
Cloud service provider (CSP) risk management: Most businesses use cloud services from multiple CSPs with varying security responsibility models. That’s where cross-platform data risk assessments come in. Well-designed risk assessments uncover data risks posed by your third-party CSPs and empower you to address them.
Mergers and acquisitions (M&A): M&A is a powerful driver of growth for many enterprises. But when companies merge or acquire another company, there’s a huge influx of new data. Data risk assessments enable you to analyze and evaluate incoming data. Its benefits don't end there: Assessments also help you create a plan of action to mitigate critical data risks and ensure secure M&A processes.
How does a data risk assessment work?
Here’s a step-by-step breakdown of a typical data risk assessment process:
1. Discovery: The first step of a data risk assessment involves discovering every single data asset across your cloud platforms (and on-premises environments, if you have any).
2. Classification: Once you’ve successfully created a data inventory, it’s important to assign classifiers based on business-specific criteria. During this step, you’ll get a clear view of what your most sensitive data is, who can access it, and why.
3. Risk analysis: This step involves using different risk evaluation methods to analyze the risk that your data assets pose. By considering and correlating various cloud contexts, you’ll uncover data risks such as exposure, misconfigured databases, overprivileged identities, and dangerous attack paths.
4. Risk reduction plan: Once you’ve completed your risk evaluation to identify data risks, it’s important to prioritize and address them in order of criticality. Creating a queue of critical risks is a good way to start.
5. Documentation: A data risk assessment isn’t complete without documentation. During this step, put together detailed notes from all the data vulnerability assessments and processes you conducted. This documentation is an important resource for regulatory audits. It can also help you optimize your risk evaluation tools and risk assessment methods for future assessments.
Data risk assessments: Common challenges and best practices
Before we explore best practices for data risk assessments, let’s explore some common challenges that you’re likely to face during the data risk assessment process.
Common challenges
Lack of visibility: For businesses with complex multi-cloud environments, it can be difficult to inventory every single data asset. If you have blind spots in your cloud environments, there’s a higher chance of shadow data and hidden risks.
Multi-tenant complexities: Like most businesses, your SaaS and PaaS infrastructure is probably multi-tenant. Multi-tenancy has its benefits but brings a couple of data-related headaches to deal with. Tackling cross-tenant data risks might appear difficult, but don’t worry: It’s nothing that strong tenant isolation frameworks can’t solve.
Compliance hurdles: Because there are so many compliance requirements and frameworks to follow (including GDPR, HIPAA, CCPA, and PCI DSS), it can be difficult to track and evaluate everything during data assessments. This problem gets even more complicated if you conduct data assessments manually or without optimal tools.
Navigating shared responsibility: No two CSPs have the exact same shared responsibility security models. Businesses that store data across different CSP platforms must know the nuances of every CSP’s shared responsibility model for data to conduct effective data risk assessments.
Integration roadblocks: In theory, connecting a security tool to cloud environments is the best way to conduct data risk assessments. Still, certain legacy solutions are integration-averse. It can take a long time to get everything set up, and even after your integrations are in place, they might be inefficient. Similarly, agent-based solutions can impact performance and speed.
Siloed processes: A data risk assessment needs to be a highly strategic and unified effort. If data risk assessment efforts are disjointed or siloed, data risks could mature into serious incidents. Without communication and collaboration between key teams and stakeholders, it’s impossible to conduct a comprehensive or accurate data risk assessment.
DSPM's Role in Data Risk Assessments
As organizations manage increasing volumes of sensitive data across diverse environments, tools like Data Security Posture Management (DSPM) have become indispensable for ongoing risk assessments. DSPM provides clear, continuous visibility into where sensitive data resides and how it is accessed, helping to identify risks such as over-permissioning, misconfigurations, and data sprawl.
DSPM tools automatically discover and classify sensitive data across various environments, including cloud services, SaaS platforms, and on-premises systems. This ensures that organizations have a complete view of their data landscape, which is essential for an accurate risk assessment.
Another reason DSPM is indispensable is its ability to contextualize risks. DSPM tools evaluate data security by identifying vulnerabilities and threats, assigning risk scores based on factors such as data sensitivity, exposure level, and regulatory requirements. This risk scoring system helps organizations prioritize which areas need immediate attention, allowing them to focus their resources on the most critical risks.
In essence, DSPM can serve as the foundation for modern data risk assessments, offering automated, continuous, and comprehensive analysis of an organization's data security posture.
Data risk assessment checklist
Before we sign off, here’s a checklist that you can use when conducting a data risk assessment:
Do we have complete visibility of our cloud environments, especially databases and storage buckets?
Do we have a comprehensive data inventory?
Do we know where our critical data is located?
Do we have a clear understanding of CSP data security shared responsibility models?
Does our data have accurate classifiers?
Do we have a prioritized view of critical data risks?
Is our data compliant with relevant frameworks?
Do we have documentation of data risks and assessment processes?
Do we have metrics and KPIs to evaluate the effectiveness of our data risk assessments?
What can we do to optimize our data risk assessment tools and processes?
Do we have a strong DSPM solution to solve our data risks and needs?
How Wiz can help with data risk assessments
Wiz is the ideal tool for cloud data risk assessments. For starters, it’s the first CNAPP platform to weave in integrated data security posture management DSPM capabilities. Wiz also provides agentless cross-platform coverage that can discover data across even the most complex cloud (and code!) environments.
When it comes to assessing and mitigating cloud data risks, Wiz is a one-stop solution that will enhance every step of your data risk assessment process, from data discovery to documentation.
Get a demo now to see how Wiz can transform your data security.
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