Role of Data Catalog in Data Security: Why It Matters in 2024

Updated February 19th, 2024
Role of data catalog in data security, data catalog security

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A data catalog can do more than just index your data - it can also serve as an instrumental tool in safeguarding your organization’s information and fortifying its security structure.

This guide examines the role data catalogs play in ensuring data security, exploring the ways they contribute to safeguarding sensitive data, streamlining compliance, and bolstering overall data governance.

Table of contents #

  1. Features of data catalog for data security
  2. How to select the right data catalog tools for data security?
  3. How does data governance help data security?
  4. How a data catalog enhanced one lender’s data security
  5. Conclusion
  6. Related reads

Features of data catalog for data security #

Key features that a data catalog provides to support data security include:

  1. Access control and permissions management
  2. Data classification and tagging
  3. Data lineage and provenance
  4. Data masking and anonymization
  5. Auditing and monitoring
  6. Encryption
  7. Integration with security tools

Let’s dive into each of these in a bit more detail.

1. Access control and permissions management #

A data catalog should have robust access control mechanisms to manage user permissions and roles. This ensures that only authorized personnel can access sensitive data, preventing unauthorized access and potential data breaches.

A robust catalog leverages mechanisms such as role-based access control (RBAC) and personas to manage security at scale. Using RBAC, you can automate access requests, driving access request permissions through an approval workflow based on predefined roles and policies.

2. Data classification and tagging #

Data catalogs can support data classification based on sensitivity levels. This classification enforces appropriate access controls and security measures based on the data’s sensitivity.

The most common example here is sensitivity tagging. By tagging certain information - such as a customer’s Personally Identifiable Information (PII) - as sensitive, you can scope access to this information to a small number of critical, pre-cleared staff. This helps ensure that information such as a customer’s government identification number or payment information never gets into the wrong hands.

Read more here.

3. Data lineage and provenance #

A data catalog should provide data lineage and impact analysis capabilities. These tools help users understand the data’s origin, transformations, and usage, which is crucial for assessing security risks.

Data lineage is critical to give business users a sense of security around their data. Using lineage, they can verify the origin of the data they’re using and ensure that it’s suitable for business decision-making.

4. Data masking and anonymization #

Data masking and anonymization techniques can be applied to sensitive data stored in the catalog. This process converts original data into a masked or anonymized form, allowing users to work with realistic data while maintaining the security of sensitive information.

5. Auditing and monitoring #

A comprehensive audit trail should be maintained, recording all interactions with the data catalog, such as data access, modifications, and metadata changes. An audit trail helps monitor and investigate any suspicious activities.

Data monitoring helps maintain data quality over time. It can also detect and raise alarms when it detects anomalies - which might be an early warning sign of tampering or intrusion.

6. Encryption #

Encryption is indispensable for any application that handles data in the modern era. This is just as true for data catalogs as it is for data stores. A data catalog should support the encryption of sensitive data, both in transit and at rest. Encryption helps protect data from unauthorized access even if there is a security breach.

7. Integration with security tools #

Integrating the data catalog with existing IAM systems ensures a centralized and consistent approach to user authentication and access control across the organization.

How to select the right data catalog tools for data security? #

Selecting the right data catalog tool for data security involves considering several factors, including:

  1. Security features
  2. Integration
  3. Scalability
  4. Usability
  5. Vendor reputation
  6. Compliance

1. Security features #

A data catalog should offer robust security features, such as access control mechanisms, encryption, data masking, and auditing capabilities. In particular, compliance monitoring ensures that your organization is conforming to all applicable data regulations, such as GDPR and HIPAA.

2. Integration #

Look for a tool that integrates well with your existing data infrastructure and security ecosystem, including data governance and data management tools.

3. Scalability #

Consider the scalability of the data catalog tool to accommodate your organization’s data growth and future needs.

4. Usability #

Choose a user-friendly tool that makes it easy for both technical and non-technical users to discover and understand data assets securely.

5. Vendor reputation #

Research the vendor’s reputation in the market, their track record in providing secure solutions, and customer reviews and feedback.

6. Compliance #

Ensure that the data catalog tool complies with relevant data privacy and security regulations applicable to your industry or region.

How does data governance help data security? #

Data governance and data security are closely related and complementary concepts. Data governance refers to the overall management framework for data, including data policies, processes, and standards that ensure data is used, accessed, and managed correctly and securely.

Here’s how data governance helps data security:

  1. Policy enforcement
  2. Data classification
  3. Access control
  4. Data quality and integrity
  5. Data lifecycle management
  6. Monitoring and auditing
  7. Data stewardship and accountability
  8. Risk management
  9. Security awareness and training
  10. Data incident response planning

1. Policy enforcement #

Data governance defines data-related policies, including security policies, that are essential for ensuring compliance and best practices in data security.

2. Data classification #

Data governance involves classifying and categorizing data based on its sensitivity and criticality. By understanding the sensitivity of data, appropriate security measures can be applied to protect high-risk data effectively.

3. Access control #

Data governance defines access control policies and permissions based on roles and responsibilities. Properly implemented, only authorized individuals can access specific data, reducing the risk of unauthorized access and data breaches.

4. Data quality and integrity #

Data governance focuses on maintaining data quality and integrity, which are crucial aspects of data security. Ensuring that data is accurate and reliable reduces the risk of security incidents caused by erroneous data.

5. Data lifecycle management #

Proper data governance includes defining data retention and disposal policies, and ensuring that data is managed securely throughout its lifecycle.

6. Monitoring and auditing #

Data governance includes monitoring and auditing processes to track data usage, access, and changes. Regular audits help identify and address potential security vulnerabilities and unauthorized activities.

7. Data stewardship and accountability #

Data governance assigns data stewardship roles and responsibilities, making individuals accountable for data security and proper data handling practices.

8. Risk management #

Data governance involves risk assessment and management, identifying potential data security risks, and implementing measures to mitigate them effectively.

9. Security awareness and training #

Data governance initiatives often include security awareness and training programs to educate employees about data security best practices, reducing the likelihood of security breaches caused by human error.

10. Data incident response planning #

Data governance helps in creating data incident response plans, enabling a swift and coordinated response to data breaches or security incidents.

How a data catalog enhanced one lender’s data security #

North American Bancard (NAB) is the sixth-largest independent acquirer in the nation, helping merchants process around USD $45 billion in purchases annually. As such, the company is always thinking about security. Despite having top-notch security in place, they’re always asking themselves: how can we make it even better?

That’s why NAB adapted Atlan to take its data governance game to the next level. Atlan not only provided features that NAB had been looking for but also features they didn’t know they needed - such as the ability to submit JIRA tickets directly from the data catalog dashboard.

Using Atlan, the company is enhancing its security even further - e.g., by using automations in Atlan to find values that ought to be masked and applying the correct sensitivity tagging.

Read the full story here.

Conclusion #

A data catalog can provide your organization with state-of-the-art data security. Atlan offers data catalogs with top-of-the-line access control, discoverability tools, monitoring dashboards, lineage tracking, and scalability to support your organization’s data security needs.

Want to see Atlan’s data security tools in action? Book a demo today.

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