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[Cyberpedia](https://www.paloaltonetworks.com/cyberpedia?ts=markdown) 2. [Network Security](https://www.paloaltonetworks.com/cyberpedia/network-security?ts=markdown) 3. [What Is Data Security Management? How to Manage Data Security](https://www.paloaltonetworks.com/cyberpedia/what-is-data-security-management?ts=markdown) Table of contents * [Why is data security management important?](#why-is-data-security-management-important) * [What is the CIA Triad's role in data security management?](#what-is-the-cia-triads-role-in-data-security-management) * [What tools, controls, and technologies support data security management?](#what-tools-controls-and-technologies-support-data-security-management) * [How to manage data security across the full data lifecycle](#how-to-manage-data-security-across-the-full-data-lifecycle) * [How to implement data security management step-by-step](#how-to-implement-data-security-management-step-by-step) * [What frameworks guide data security management?](#what-frameworks-guide-data-security-management) * [Who owns data security management in an organization?](#who-owns-data-security-management-in-an-organization) * [Top 5 common data security management pitfalls](#top-5-common-data-security-management-pitfalls) * [Comparing data security management, information security management, and cybersecurity management](#comparing-data-security-management) * [Data security management FAQs](#data-security-management-faqs) # What Is Data Security Management? How to Manage Data Security 5 min. read Table of contents * [Why is data security management important?](#why-is-data-security-management-important) * [What is the CIA Triad's role in data security management?](#what-is-the-cia-triads-role-in-data-security-management) * [What tools, controls, and technologies support data security management?](#what-tools-controls-and-technologies-support-data-security-management) * [How to manage data security across the full data lifecycle](#how-to-manage-data-security-across-the-full-data-lifecycle) * [How to implement data security management step-by-step](#how-to-implement-data-security-management-step-by-step) * [What frameworks guide data security management?](#what-frameworks-guide-data-security-management) * [Who owns data security management in an organization?](#who-owns-data-security-management-in-an-organization) * [Top 5 common data security management pitfalls](#top-5-common-data-security-management-pitfalls) * [Comparing data security management, information security management, and cybersecurity management](#comparing-data-security-management) * [Data security management FAQs](#data-security-management-faqs) 1. Why is data security management important? * [1. Why is data security management important?](#why-is-data-security-management-important) * [2. What is the CIA Triad's role in data security management?](#what-is-the-cia-triads-role-in-data-security-management) * [3. What tools, controls, and technologies support data security management?](#what-tools-controls-and-technologies-support-data-security-management) * [4. How to manage data security across the full data lifecycle](#how-to-manage-data-security-across-the-full-data-lifecycle) * [5. How to implement data security management step-by-step](#how-to-implement-data-security-management-step-by-step) * [6. What frameworks guide data security management?](#what-frameworks-guide-data-security-management) * [7. Who owns data security management in an organization?](#who-owns-data-security-management-in-an-organization) * [8. Top 5 common data security management pitfalls](#top-5-common-data-security-management-pitfalls) * [9. Comparing data security management, information security management, and cybersecurity management](#comparing-data-security-management) * [10. Data security management FAQs](#data-security-management-faqs) ![A diagram illustrating the data lifecycle, a continuous circular process around a central server rack protected by a shield. The steps, connected by dashed lines, are: 1. Create (represented by a pencil and plus sign), 2. Store (represented by a file folder on a server rack), 3. Use (represented by a person's head/profile), 4. Transmit (represented by data moving between two server racks via radio waves), and 5. Dispose (represented by a trash can over a server rack).](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/what-is-data-security-management-video-thumbnail.png) close Data security management is the practice of protecting data from unauthorized access, alteration, or loss throughout its lifecycle. It includes the development and enforcement of policies, processes, and controls that ensure data remains secure during creation, storage, use, and disposal. Effective data security management aligns technical safeguards with organizational oversight to reduce risk and support compliance. ## Why is data security management important? [Data security](https://www.paloaltonetworks.com/cyberpedia/what-is-data-security) management is important because it creates a consistent, organization-wide approach to protecting [sensitive data](https://www.paloaltonetworks.com/cyberpedia/sensitive-data). Without it, security controls are often uneven, reactive, or incomplete. Especially as data environments grow more complex. Most organizations operate in hybrid environments and rely on external providers for infrastructure, storage, and collaboration. Data is constantly being accessed, modified, shared, and stored across systems and teams. "92% of workloads are now hosted on some form of cloud platform, indicating a significant shift from traditional on-premises solutions. Only 8% of workloads remain solely on-premises, showing a substantial move towards cloud-based infrastructure across various industries." [- Rackspace, The 2025 State of Cloud Report](https://www.rackspace.com/lp/2025-state-cloud-report) In many cases, no single group has full visibility or authority over how that data is handled. That makes it harder to identify weak points. And easier for something to go wrong. Here's where data security management makes a difference: It gives structure to how data protection is planned and enforced. That includes how data is classified, who can access it, how it's monitored, and what happens if it's lost or exposed. It also establishes accountability. Different roles---from security teams to business units---understand what they're responsible for and how their actions impact data risk. And the cost of getting it wrong keeps rising. "As of 2024, the global average cost of a data breach is $4.88 million, marking a 10% increase from the previous year." [- IBM, Cost of a Data Breach Report 2024](https://www.ibm.com/reports/data-breach) This kind of clarity helps reduce the likelihood of mistakes, misconfigurations, and missed threats. It also makes it easier to meet compliance requirements, investigate incidents, and recover faster when needed. In short, data security management moves data protection from a patchwork of efforts to a coordinated, measurable program. | ***Further reading:** [What Is Data-Centric Security?](https://www.paloaltonetworks.com/cyberpedia/data-centric-security)* ## What is the CIA Triad's role in data security management? The CIA Triad refers to three core principles: * Confidentiality * Integrity * Availability ![Three overlapping circles form a triangular layout representing the CIA Triad. Each circle contains a distinct icon and label: the top circle is bright blue with a padlock icon and labeled 'Confidentiality', the bottom left circle is teal with a checkmark icon and labeled 'Availability', and the bottom right circle is orange with a scale icon and labeled 'Integrity'. To the right of the diagram, 'Confidentiality' is defined as 'Restrict access to data based on need. Prevent unauthorized viewing or sharing.' Below, 'Integrity' is defined as 'Keep data accurate and unaltered. Protect against unauthorized changes.' To the left of the diagram, 'Availability' is defined as 'Ensure data is accessible when needed. Minimize downtime and disruptions.' Thin gray lines connect each label to its corresponding circle.](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_1-CIA-Triad.png "Three overlapping circles form a triangular layout representing the CIA Triad. Each circle contains a distinct icon and label: the top circle is bright blue with a padlock icon and labeled 'Confidentiality', the bottom left circle is teal with a checkmark icon and labeled 'Availability', and the bottom right circle is orange with a scale icon and labeled 'Integrity'. To the right of the diagram, 'Confidentiality' is defined as 'Restrict access to data based on need. Prevent unauthorized viewing or sharing.' Below, 'Integrity' is defined as 'Keep data accurate and unaltered. Protect against unauthorized changes.' To the left of the diagram, 'Availability' is defined as 'Ensure data is accessible when needed. Minimize downtime and disruptions.' Thin gray lines connect each label to its corresponding circle.") These principles are used to evaluate and enforce the protection of data across its lifecycle. Data security management uses them as the foundation for how safeguards are planned, applied, and measured. **Confidentiality** focuses on limiting access to data based on need and risk. It prevents unauthorized exposure through controls like authentication, [encryption](https://www.paloaltonetworks.com/cyberpedia/data-encryption), and role-based access. **Integrity** ensures that data remains accurate and complete. That includes protecting it from unauthorized changes and validating that it hasn't been tampered with. **Availability** ensures that data remains usable when needed. This requires resilient systems, backup plans, and monitoring to reduce downtime and service disruption. Why does this matter? Because data security controls are only effective when they address all three areas. Overemphasizing one---like confidentiality---without considering availability or integrity can introduce new risks. The CIA Triad provides a balanced framework that helps organizations protect data in practical, measurable ways. It also supports clearer decisions when classifying data, assigning protections, and [responding to incidents](https://www.paloaltonetworks.com/cyberpedia/what-is-incident-response). ## What tools, controls, and technologies support data security management? ![A centralized circular icon labeled 'Controls' sits in the middle of the image, flanked by two smaller colored circles: one blue on the left labeled 'Tools' with a wrench and gear icon, and one teal on the right labeled 'Technologies' with a chip icon. Six items branch from the Tools circle: 'Data loss prevention (DLP)', 'Identity providers (IdPs)', 'Cloud access security brokers (CASBs)', 'Endpoint detection \& response (EDR)', 'Backup \& recovery software', and 'Security information \& event management (SIEM)'. From the Technologies circle, six items branch outward: 'Public key infrastructure (PKI)', 'Transport layer security (TLS)', 'Tokenization', 'Federated identity', and 'Zero trust architectures'. Below the central Controls circle, six vertical items are listed: 'Encryption', 'Data classification', 'Access control', 'Segmentation', 'Audit logging', and 'Monitoring \& alerting'. All elements are organized in a clean, symmetrical diagram under the title 'Data security management tools, controls, \& technologies'.](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_2-Data.png "A centralized circular icon labeled 'Controls' sits in the middle of the image, flanked by two smaller colored circles: one blue on the left labeled 'Tools' with a wrench and gear icon, and one teal on the right labeled 'Technologies' with a chip icon. Six items branch from the Tools circle: 'Data loss prevention (DLP)', 'Identity providers (IdPs)', 'Cloud access security brokers (CASBs)', 'Endpoint detection & response (EDR)', 'Backup & recovery software', and 'Security information & event management (SIEM)'. From the Technologies circle, six items branch outward: 'Public key infrastructure (PKI)', 'Transport layer security (TLS)', 'Tokenization', 'Federated identity', and 'Zero trust architectures'. Below the central Controls circle, six vertical items are listed: 'Encryption', 'Data classification', 'Access control', 'Segmentation', 'Audit logging', and 'Monitoring & alerting'. All elements are organized in a clean, symmetrical diagram under the title 'Data security management tools, controls, & technologies'.") Data security management relies on a wide range of tools, controls, and technologies that work together to protect data across its lifecycle. Here's how to break it down: ### Tools These are the systems and platforms used to enforce policies, monitor activity, and respond to risks. * **[Data loss prevention (DLP)](https://www.paloaltonetworks.com/cyberpedia/what-is-data-loss-prevention-dlp):** Blocks unauthorized sharing or transfer of sensitive data * **[Security information and event management (SIEM)](https://www.paloaltonetworks.com/cyberpedia/what-is-security-information-and-event-management-siem):** Collects and analyzes logs to detect and alert on threats * **[Cloud access security brokers (CASBs)](https://www.paloaltonetworks.com/cyberpedia/what-is-a-casb-cloud-access-security-broker):** Enforce data security policies across SaaS applications * **[Endpoint detection and response (EDR)](https://www.paloaltonetworks.com/cyberpedia/what-is-endpoint-detection-and-response-edr):** Monitors endpoints for signs of compromise * **Identity providers (IdPs):** Manage authentication and enable single sign-on * **Backup and recovery software:** Restores data after accidental loss or corruption ### Controls Controls are the safeguards---administrative, technical, or physical---that reduce risk and enforce security. * **[Access control](https://www.paloaltonetworks.com/cyberpedia/access-control):** Restricts access based on roles or attributes * **Encryption:** Protects data in transit and at rest by making it unreadable without a key * **[Data classification](https://www.paloaltonetworks.com/cyberpedia/data-classification):** Labels data by sensitivity to guide handling and storage * **Audit logging:** Records access and activity to support investigation and compliance * **Segmentation:** Limits lateral movement by separating data environments * **Monitoring and alerting:** Detects anomalous access patterns or usage ### Technologies These are the underlying mechanisms that enable secure data protection strategies and toolsets. * **Public key infrastructure (PKI):** Supports encryption, digital signatures, and identity validation * **Transport layer security (TLS):** Secures data in motion between systems * **Tokenization:** Replaces sensitive data with non-sensitive placeholders * **Federated identity:** Enables secure access across systems with shared authentication * **[Zero trust architectures](https://www.paloaltonetworks.com/cyberpedia/what-is-a-zero-trust-architecture):** Assume no implicit trust and validate each access request independently These categories overlap in practice. But separating them helps clarify how data security management is implemented and maintained. ## How to manage data security across the full data lifecycle ![A horizontal sequence of seven labeled icons illustrates the stages of the data security lifecycle, each enclosed in a colored circle. From left to right, the stages are: 'Identify \& classify data' with a gray icon of stacked documents, 'Assign ownership \& handling rules' with a light blue icon of three user profiles, 'Protect data during use' with a red icon of a shield and gear, 'Secure data in transit' with a blue icon of an airplane flying over a document, 'Encrypt \& retain data at rest' with a teal icon of a server or hard drive, 'Safely delete or sanitize data' with a purple icon of a trash bin, and 'Maintain auditability' with a dark gray icon of a document and magnifying glass. Each icon corresponds to its label above or below and visually represents its phase in the data lifecycle. The entire visual is headed by the title 'Data security lifecycle'.](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_3-Data.png "A horizontal sequence of seven labeled icons illustrates the stages of the data security lifecycle, each enclosed in a colored circle. From left to right, the stages are: 'Identify & classify data' with a gray icon of stacked documents, 'Assign ownership & handling rules' with a light blue icon of three user profiles, 'Protect data during use' with a red icon of a shield and gear, 'Secure data in transit' with a blue icon of an airplane flying over a document, 'Encrypt & retain data at rest' with a teal icon of a server or hard drive, 'Safely delete or sanitize data' with a purple icon of a trash bin, and 'Maintain auditability' with a dark gray icon of a document and magnifying glass. Each icon corresponds to its label above or below and visually represents its phase in the data lifecycle. The entire visual is headed by the title 'Data security lifecycle'.") Data security management isn't a one-time task. It has to follow the full lifecycle of the data. From creation to disposal. Each stage carries its own risks and requires specific controls to reduce exposure and maintain integrity. 1. **Identify and classify data:** Start by determining what kinds of data your organization collects, creates, or receives. Classify it by sensitivity to guide how it should be protected. 2. **Assign ownership and handling rules:** Define who is responsible for the data. Set clear rules for how it should be accessed, used, shared, and stored. 3. **Protect data during use:** Restrict access using role-based controls. Monitor access behavior to detect misuse. Segment high-risk environments to limit exposure. 4. **Secure data in transit:** Use encryption and secure protocols when data moves across systems, applications, or networks. Validate that transfers only occur through approved channels. 5. **Encrypt and retain data at rest:** Store data securely using encryption, backups, and physical or logical access controls. Apply retention schedules based on legal and operational needs. 6. **Safely delete or sanitize data:** When data is no longer needed, securely delete or sanitize it to prevent recovery. Use tools that ensure data is unrecoverable if media is reused. 7. **Maintain auditability:** Record relevant actions like access, modification, and deletion. This supports accountability, incident response, and compliance. Lifecycle management only works when each phase is addressed intentionally. Controls need to stay aligned with how and where the data is used over time. ## How to implement data security management step-by-step ![A visual guide titled 'How to implement data security management step-by-step' presents seven steps in a structured, left-to-right and top-to-bottom layout. Each step is marked with a red numbered circle and accompanied by a corresponding icon. Step 1, 'Define governance \& scope', shows a briefcase icon and advises establishing ownership of the data security program. Step 2, 'Identify \& classify data', includes a checklist icon and focuses on creating a data inventory. Step 3, 'Assess risks \& requirements', uses a target icon and emphasizes evaluating exposures and potential threats. Step 4, 'Select controls \& define policies', features a gear icon and instructs teams to choose controls that mitigate identified risks. Step 5, 'Implement tools \& technical safeguards', has a crossed wrench and screwdriver icon and recommends selecting tools that align with policy and architecture. Step 6, 'Monitor, audit, \& update', shows a magnifying glass icon and advises tracking data use and modifications. Step 7, 'Train staff \& enforce accountability', includes a person icon and underscores the importance of clear role definitions and responsibilities. Each step is paired with a brief supporting explanation in smaller black text.](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_4-How.png "A visual guide titled 'How to implement data security management step-by-step' presents seven steps in a structured, left-to-right and top-to-bottom layout. Each step is marked with a red numbered circle and accompanied by a corresponding icon. Step 1, 'Define governance & scope', shows a briefcase icon and advises establishing ownership of the data security program. Step 2, 'Identify & classify data', includes a checklist icon and focuses on creating a data inventory. Step 3, 'Assess risks & requirements', uses a target icon and emphasizes evaluating exposures and potential threats. Step 4, 'Select controls & define policies', features a gear icon and instructs teams to choose controls that mitigate identified risks. Step 5, 'Implement tools & technical safeguards', has a crossed wrench and screwdriver icon and recommends selecting tools that align with policy and architecture. Step 6, 'Monitor, audit, & update', shows a magnifying glass icon and advises tracking data use and modifications. Step 7, 'Train staff & enforce accountability', includes a person icon and underscores the importance of clear role definitions and responsibilities. Each step is paired with a brief supporting explanation in smaller black text.") Data security management isn't just a matter of deploying tools. It's a structured discipline that brings together policies, safeguards, and operational practices. Here's how to implement it step by step. ### Step 1: Define governance and scope Start by establishing who owns the data security program. * Identify business objectives, risk tolerance, and legal or regulatory requirements. * Set the scope based on data types, systems, and environments you need to secure. * Then formalize ownership and oversight to support long-term accountability. ***Tip:*** *Don't forget to include both technical and business stakeholders in the governance structure. This helps bridge operational gaps and ensures data policies are practical across teams.* ### Step 2: Identify and classify data Create and maintain an inventory of the data your organization handles. * Classify it based on sensitivity, regulatory exposure, or business criticality. * Use that classification to drive handling rules and protection levels. * Make sure classification aligns with access control and retention policies. ### Step 3: Assess risks and requirements Evaluate where data is exposed and what could go wrong. * Include internal threats, third-party risk, and system vulnerabilities. * Map these risks to specific controls and requirements tied to business needs or compliance standards. * A strong risk register helps keep priorities focused and defensible. | ***Further reading:** [What Is a Data Risk Assessment?](https://www.paloaltonetworks.com/cyberpedia/data-risk-assessment)* ### Step 4: Select controls and define policies Decide which controls you'll use to mitigate identified risks. * That includes technical controls like access restrictions, encryption, and monitoring. * It also includes administrative controls like data handling policies, acceptable use, and retention rules. * Policies should be practical, enforceable, and reviewed regularly. ***Tip:*** *Prioritize controls that can be enforced consistently across environments. For example, controls that span cloud and on-prem systems reduce complexity and policy drift.* | ***Further reading:*** * [*What Is Data Access Governance?*](https://www.paloaltonetworks.com/cyberpedia/data-access-governance) * [*Data Security Policies: Why They Matter and What They Contain*](https://www.paloaltonetworks.com/cyberpedia/data-security-policy) ### Step 5: Implement tools and technical safeguards Choose tools that support your policies and align with your architecture. **For example:** DLP for data in motion, encryption for data at rest, and access management tools for role enforcement. Integrate controls into workflows so protections are automatic, not manual. ### Step 6: Monitor, audit, and update Track how data is used, accessed, and modified. * Review audit logs, alert on anomalies, and test controls regularly. * As your environment changes, update controls and policies to reflect new risks or changes in data flow. * Monitoring should inform not just alerts, but governance decisions. ***Tip:*** *Use monitoring data to identify low-value or unused data assets. This can guide clean-up efforts and reduce exposure by eliminating unnecessary risk surfaces.* People are a critical part of data protection. Make sure roles are clearly defined and that staff understand their responsibilities. Deliver targeted training and reinforce policies through onboarding, reviews, and corrective action processes. Training should reflect real workflows, not just abstract threats. ***Tip:*** *Reinforce accountability by tracking policy acknowledgment and completion rates. This helps surface gaps in awareness and supports stronger audit readiness.* | ***Further reading:** [Top 12 Data Security Best Practices \[+ Tips, Tricks, \& FYIs\]](https://www.paloaltonetworks.com/cyberpedia/data-security-best-practices)* ## What frameworks guide data security management? You don't have to start from scratch when building a data security management program. Lean on well-established frameworks to define goals, select controls, and measure progress. Note that these frameworks don't all serve the same purpose. Some offer high-level governance guidance. Others are more operational or control-focused. And some help translate policies into specific technologies or program activities. But all of the frameworks below serve as the foundation for effective data security management. While each has a different lens, they all help teams stay aligned with risk, regulation, and real-world threats. | Data security management frameworks ||| | Framework | Primary focus | How it supports data security management | |---------------------------------------------------------------------------------------------------|-----------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------| | [NIST Cybersecurity Framework (CSF) 2.0](https://nvlpubs.nist.gov/nistpubs/CSWP/NIST.CSWP.29.pdf) | Risk-based cybersecurity outcomes | Helps organizations define a target security posture, prioritize actions, and map outcomes across governance, protection, detection, response, and recovery. | | [NIST SP 800-53 Rev. 5](https://csrc.nist.gov/pubs/sp/800/53/r5/upd1/final) | Security and privacy controls | Provides a catalog of detailed controls used to enforce confidentiality, integrity, and availability across systems, data types, and environments. | | [ISO/IEC 27001:2022](https://www.iso.org/standard/27001) | Information security management systems | Defines how to establish, implement, maintain, and improve a comprehensive ISMS based on risk assessment and treatment. | | [COBIT 2019](https://store.isaca.org/s/store#/store/browse/detail/a2S4w000004Ko9cEAC) | Governance of enterprise IT | Offers a governance framework that connects enterprise goals with IT objectives, including data protection, control objectives, and performance monitoring. | | [CIS Controls v8](https://www.cisecurity.org/controls/v8) | Operational safeguards | Offers prioritized, implementation-focused controls that directly support technical enforcement of data security policies across endpoints, users, and networks. | ## Who owns data security management in an organization? Ownership of data security management depends on the structure, size, and maturity of the organization. But across most frameworks, the responsibility sits with clearly designated roles tied to risk governance and information security. Not general IT. That distinction matters. Here's why: Effective data security requires oversight, authority, and accountability. Which means someone has to be responsible for making policy decisions, allocating resources, and ensuring compliance. That's typically a C-level or senior leadership role---such as a Chief Information Security Officer (CISO), Chief Risk Officer (CRO), or Chief Data Officer (CDO)---depending on how the organization is structured. Important: These roles don't operate alone. Security, risk, legal, compliance, and privacy teams all share responsibilities. But the ultimate ownership should be formalized. Frameworks we referenced earlier, like the NIST CSF and COBIT, reinforce this by emphasizing defined roles, delegated authority, and continuous reporting on performance and risk posture. Without that structure, it's easy for accountability to diffuse. Or disappear. ## Top 5 common data security management pitfalls Even with the right tools and policies in place, data security management can still fall short. Small gaps add up quickly. And often show up in the same familiar places. Success depends on consistent execution across people, processes, and systems. Here are five common pitfalls that quietly undermine even well-designed data security programs: ### 1. Incomplete data classification Failing to accurately classify data is one of the most common weak points. Without clear labels for sensitivity levels, organizations can't confidently enforce access, encryption, or retention policies. ![A table titled 'Incomplete data classification scenario' displays five rows of data assets with columns labeled 'Data type,' 'System,' 'Sensitivity,' and 'Classification.' The first row lists 'Customer name (with ID/email)' stored in a CRM system with 'Moderate' sensitivity marked by an orange dot and classified as 'Internal.' The second row shows 'Social Security #' in a billing platform with 'High' sensitivity indicated by a red dot and also classified as 'Internal.' The third row lists 'Marketing images (unpublished)' in cloud storage with both 'Low' (green dot) and 'Moderate' (orange dot) sensitivity values and a classification of 'Public,' suggesting a mismatch. The fourth row, 'Credit card number' in a support database, has 'High' sensitivity marked by a red dot but is labeled 'Unclassified' and outlined with a red border to highlight the issue. The final row shows 'HR salary records' on a shared drive with 'High' sensitivity marked by a red dot and a classification of 'Confidential.' Below the table, a caption reads: 'Incomplete classification often looks like this—missing values, default labels, or mismatched risk levels.'](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_5.png "A table titled 'Incomplete data classification scenario' displays five rows of data assets with columns labeled 'Data type,' 'System,' 'Sensitivity,' and 'Classification.' The first row lists 'Customer name (with ID/email)' stored in a CRM system with 'Moderate' sensitivity marked by an orange dot and classified as 'Internal.' The second row shows 'Social Security #' in a billing platform with 'High' sensitivity indicated by a red dot and also classified as 'Internal.' The third row lists 'Marketing images (unpublished)' in cloud storage with both 'Low' (green dot) and 'Moderate' (orange dot) sensitivity values and a classification of 'Public,' suggesting a mismatch. The fourth row, 'Credit card number' in a support database, has 'High' sensitivity marked by a red dot but is labeled 'Unclassified' and outlined with a red border to highlight the issue. The final row shows 'HR salary records' on a shared drive with 'High' sensitivity marked by a red dot and a classification of 'Confidential.' Below the table, a caption reads: 'Incomplete classification often looks like this—missing values, default labels, or mismatched risk levels.'") This leaves sensitive information exposed or improperly handled. ### 2. Overly permissive access controls It's easy to grant too much access for the sake of convenience. But when users have access beyond what they need, it increases the risk of unauthorized exposure. Especially if credentials are compromised. ![A table titled 'Overly permissive access controls' shows three user access scenarios with five columns: 'User,' 'Role,' 'System accessed,' 'Access level,' and 'Notes.' The first row lists John Martinez, a Marketing Manager with 'Full admin' access to the Customer database, noted as 'Should only have read access.' The second row lists Sarah Lee, a Sales Associate with 'Write/edit' access to Financial reporting, noted as 'No business need for this access.' The third row shows System account 45 with an 'Unassigned' role and 'Read access' to HR records, noted as 'Not linked to any user.' Each access level—'Full admin,' 'Write/edit,' and 'Read access'—is enclosed in a red border. A caption below the table states: 'These users have access rights that exceed their role or business need. Least privilege would limit this exposure.'](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_6-Overly.png "A table titled 'Overly permissive access controls' shows three user access scenarios with five columns: 'User,' 'Role,' 'System accessed,' 'Access level,' and 'Notes.' The first row lists John Martinez, a Marketing Manager with 'Full admin' access to the Customer database, noted as 'Should only have read access.' The second row lists Sarah Lee, a Sales Associate with 'Write/edit' access to Financial reporting, noted as 'No business need for this access.' The third row shows System account 45 with an 'Unassigned' role and 'Read access' to HR records, noted as 'Not linked to any user.' Each access level—'Full admin,' 'Write/edit,' and 'Read access'—is enclosed in a red border. A caption below the table states: 'These users have access rights that exceed their role or business need. Least privilege would limit this exposure.'") Least privilege should be the default. ### 3. Lack of visibility into data flows If data flows aren't mapped---especially across third-party providers and cloud environments---it's difficult to monitor or control how sensitive data is stored, processed, or shared. You can't protect what you don't understand. ### 4. Stale or unmanaged data inventories Inventories aren't one-and-done. But many teams don't revisit them regularly. ![A side-by-side visual comparison titled 'What happens when no one updates the data inventory' contrasts two tables labeled 'Initial inventory' and 'Current reality.' The 'Initial inventory' table includes three rows: 'Customer records' stored in the 'CRM system' owned by 'Sales ops' and last verified 'This quarter'; 'HR files' stored on a 'Shared drive' owned by 'HR manager' and also verified 'This quarter'; and 'Financial data' in the 'ERP system' owned by 'Finance lead' with the same verification status. The 'Current reality' table includes three different entries: 'Customer records' in the 'CRM system' still owned by 'Sales ops' but with a last verified status of 'Unknown' marked in red; 'HR files' still in the 'Shared drive' but now owned by 'Unassigned' and last verified '2 years ago' in red text; and 'Marketing exports' stored in a 'Shadow file share' with 'Unknown' ownership and a verification status of 'Never,' also in red. Between the two tables is a vertical arrow showing a timeline progression from 'Initial inventory' to 'Current reality.' On the left, accompanying text reads: 'The documented inventory looks complete. But the actual environment tells a different story. Over time, data ends up in places no one's tracking—or even knows about.'](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_7-What.png) That means outdated mappings, forgotten repositories, or untracked [shadow IT](https://www.paloaltonetworks.com/cyberpedia/shadow-it). All of which can lead to data loss or noncompliance. | ***Further reading:** [What Is a Data Flow Diagram?](https://www.paloaltonetworks.com/cyberpedia/data-flow-diagram)* ### 5. Poor enforcement of data retention policies Retention rules exist for a reason. But without enforcement, sensitive data may be kept indefinitely. Or deleted too soon. ![A comparison chart titled 'What poor retention enforcement looks like' displays two columns: 'Without enforcement' in red on the left and 'With enforcement' in green on the right. The first row labeled 'File retention' shows that without enforcement, the file 'invoice\_0423.csv' is still present after 120 days, while with enforcement, the same file is auto-deleted at 30 days. The second row labeled 'Sensitive data folder' shows that the 'HR\_exports/' folder is unmonitored for over a year without enforcement, whereas with enforcement, the same folder is reviewed quarterly with retention applied. The third row labeled 'Deletion audit trail' shows no log or confirmation of deletion events without enforcement, compared to deletion being logged and verified with enforcement. The final row labeled 'Retention schedule' shows that without enforcement it exists only as a policy document and is not enforced, while with enforcement it is mapped to data types and actively applied. Each row uses red warning icons on the left and green checkmark icons on the right to visually reinforce the contrast in retention practices.](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/what-is-data-security-management/data-security-management_8.png "A comparison chart titled 'What poor retention enforcement looks like' displays two columns: 'Without enforcement' in red on the left and 'With enforcement' in green on the right. The first row labeled 'File retention' shows that without enforcement, the file 'invoice_0423.csv' is still present after 120 days, while with enforcement, the same file is auto-deleted at 30 days. The second row labeled 'Sensitive data folder' shows that the 'HR_exports/' folder is unmonitored for over a year without enforcement, whereas with enforcement, the same folder is reviewed quarterly with retention applied. The third row labeled 'Deletion audit trail' shows no log or confirmation of deletion events without enforcement, compared to deletion being logged and verified with enforcement. The final row labeled 'Retention schedule' shows that without enforcement it exists only as a policy document and is not enforced, while with enforcement it is mapped to data types and actively applied. Each row uses red warning icons on the left and green checkmark icons on the right to visually reinforce the contrast in retention practices.") Both increase risk. And neither meets the requirements of most regulatory frameworks. ## Comparing data security management, information security management, and cybersecurity management These three terms are often used interchangeably. But they don't mean the same thing. **Data security management focuses strictly on protecting data. It's concerned with how data is classified, accessed, transmitted, stored, and disposed of**, regardless of format or location. The goal is to safeguard data's confidentiality, integrity, and availability. **Information security management is broader. It covers data but also includes the protection of other types of information assets,** such as documentation, intellectual property, and business processes. This approach integrates physical security, personnel practices, and technical controls to safeguard organizational knowledge. **Cybersecurity management zeroes in on digital systems and networks. It involves identifying and responding to threats that target IT infrastructure,** including [malware](https://www.paloaltonetworks.com/cyberpedia/what-is-malware), unauthorized access, and [denial-of-service attacks](https://www.paloaltonetworks.com/cyberpedia/what-is-a-denial-of-service-attack-dos). While data protection is a part of this, the emphasis is on system and network-level security. In short: Data security is a subset of information security, which itself overlaps with but is not equivalent to cybersecurity. ![Icon of databases](https://www.paloaltonetworks.com/content/dam/pan/en_US/images/cyberpedia/benefits-of-sd-wan/icon-data-security-best-practices.svg) Confidently choose the right data loss prevention solution for your organization Featuring the *Gartner 2025 Market Guide for Data Loss Prevention*. --- [Download](https://www.paloaltonetworks.com/resources/research/gartner-2025-market-guide-data-loss-prevention) ## Data security management FAQs ### What is the role of data security management in an organization? It creates a structured, organization-wide approach to protect data throughout its lifecycle. It aligns controls, policies, and accountability to reduce risk, enforce compliance, and support incident response. ### What are examples of data security management tools? Examples include DLP for preventing data leakage, SIEM for monitoring threats, CASBs for cloud enforcement, IdPs for access control, EDR for endpoint protection, and backup tools for recovery. ### How is data security management different from cybersecurity? Data security focuses on protecting data itself. Cybersecurity targets broader threats to systems and networks. Data security is more specific, while cybersecurity includes infrastructure-level protection. ### Who is responsible for managing data security? Ownership typically lies with a senior role like a CISO or CRO. Security, risk, compliance, and privacy teams support it. Frameworks recommend formalized authority and clear accountability. ### Why do data security programs fail? Common issues include incomplete classification, overly broad access, poor visibility, outdated inventories, and weak policy enforcement. These gaps expose sensitive data and increase compliance risk. ### What frameworks guide data security management? Relevant frameworks include NIST CSF, NIST SP 800-53, ISO/IEC 27001, COBIT 2019, and CIS Controls v8. Each supports different aspects---from governance to operational control. Related Content [Blog: A Reliable Data Protection Strategy Hinges Upon Data Detection Find out why visibility of all corporate data is fundamental to enabling data protection.](https://www.paloaltonetworks.com/blog/network-security/a-reliable-data-protection-strategy-hinges-upon-highly-accurate-data-detection/?ts=markdown) [Blog: Maintaining Data Security When Your Workforce is Remote Learn how implementing data protection for the remote workforce is the formula to success.](https://www.paloaltonetworks.com/blog/network-security/maintaining-data-security-when-your-workforce-is-remote/?ts=markdown) [Blog: Contain the SaaS Explosion with a Redefined Approach to CASB See why consistent SaaS security = protected users, apps, and data.](https://www.paloaltonetworks.com/blog/network-security/contain-the-saas-explosion-with-a-redefined-approach-to-casb/?ts=markdown) [Guide: Next-Generation CASB for Dummies Discover what a next-gen CASB is and how it keeps SaaS applications and data secure.](https://www.paloaltonetworks.com/resources/ebooks/sase-for-dummies?ts=markdown) ![Share page on facebook](https://www.paloaltonetworks.com/etc/clientlibs/clean/imgs/resources/facebook-circular-icon.svg) ![Share page on linkedin](https://www.paloaltonetworks.com/etc/clientlibs/clean/imgs/resources/linkedin-circular-icon.svg) [![Share page by an email](https://www.paloaltonetworks.com/etc/clientlibs/clean/imgs/resources/email-circular-icon.svg)](mailto:?subject=What%20Is%20Data%20Security%20Management%3F%20How%20to%20Manage%20Data%20Security&body=Data%20security%20management%20is%20the%20practice%20of%20protecting%20data%20from%20unauthorized%20access%2C%20alteration%2C%20or%20loss%20throughout%20its%20lifecycle.%20at%20https%3A//www.paloaltonetworks.com/cyberpedia/what-is-data-security-management) Back to Top {#footer} ## 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