Sensitive data is always on the brink of exposure, especially when organizations lack contextual data intelligence, data governance and a data security posture management strategy. Lack of data security management is one of the core reasons why, in the second quarter of 2025, nearly 94 million data records were leaked in data breaches, impacting millions of individuals worldwide.
Despite realizing the risks associated with the improper handling of data, most organizations take data for granted until it is too late. It’s no secret that every byte of data serves as the backbone of business strategic decision-making, and ensuring it remains confidential, accurate, and available at all times is core to unlocking its true potential.
This is where data security management extends from being a choice and a reactive approach to a core component of a robust data security posture management strategy.
What is Data Security Management?
Data security management is a broad-ranging framework that consists of the development and deployment of data security policies, processes, tools, and governance practices aimed at protecting sensitive data from unauthorized access, alteration, and inadvertent data exposure throughout the data lifecycle.
It’s a critical, high-priority framework that ensures sensitive data remains secure during creation, storage, use, and disposal. It also ensures that data is protected from malicious actors at all times, whether it is being utilized, in transit, or at rest.
Why is Data Security Management Important?
Data is the fuel powering businesses and driving growth. However, this can quickly turn into an organization’s biggest nightmare if not secured with the right practices, strategies, policies, and modern-day automation tools.
Despite data sprawling across the digital landscape and data processing at an all-time high, most organizations still utilize legacy models to handle data security. Ignoring the rise in cyberthreats and placing data security as an afterthought is precisely why data security management is more important than ever to protect crown jewels from data exposure.
Lack of data visibility and transparency further fuels vulnerabilities that attackers can exploit, resulting in a data breach. This is where data security management is extremely important, as it establishes a consistent, organization-wide approach to protecting sensitive data.
As an organization’s data stores accelerate and data is accessed, modified, stored, and shared across networks, systems, and teams, a baseline data security management posture and strategy is core to ensuring data handling practices comply with ethical values as well as regulatory requirements. This is particularly important as data environments tend to increase and grow more complex.
Inability to implement adequate data security measures required by global regulations such as GDPR, CCPA/CPRA, HIPAA, and others can lead to severe non-compliance penalties as well as reputational damage. Additionally, let’s not discount the operational disruption organizations can face, resulting in lost revenue and unnecessary legal exposure.
Core Components of Data Security Management
At its core, data security management involves a variety of strategies and practices to protect sensitive data from unauthorized access, use, or disclosure. Core components include:
A. Identifying and Classifying Data
You can’t protect what you can’t see. The preliminary step in ensuring data security is to start by determining what kinds of data your organization collects, creates, stores, or shares with third parties. Once identified, classification can begin, and sensitivity levels can be assigned to make it visible which data requires what kinds of protection.
B. Assigning Ownership and Data Handling Guidelines
There’s no accountability without ownership. Dedicate a resource or a team that’s solely responsible for onboarding data security measures that include adopting the latest data security practices, policies, tools and educating individuals who handle data. Define clear data handling guidelines, role-based access controls and track data across its lifecycle.
C. Ensuring Data Protection
Data is in transit across networks, systems and cloud services at all times. It’s also residing in silos, dark systems, and on-premises at rest. No matter at which stage data is in its lifecycle, it must be protected. Additionally, data access must be monitored and logged to identify misuse and limit exposure, especially in hyperscale data environments.
D. Data Governance and Compliance
Data governance is critical to ensuring that data is accurate, secure, available, and usable through a set of policies, practices, and processes. This ensures compliance with evolving data privacy laws, including the GDPR, CCPA/CPRA, HIPAA, GLBA, SOX, DORA, etc.
E. Risk Assessments
Managing risk entails conducting regular risk assessments that provide a clear picture of the current security posture. It flags vulnerabilities, gaps and threats that could weaken data security posture and result in data exposure. Assessments include a readiness assessment, data protection impact assessment (DPIA), transfer impact assessment (TIA), vendor risk assessment (VRA), etc.
Common Challenges of Data Security
Despite the several benefits of having a robust data security posture, organizations continue to struggle with protecting their data assets. Common challenges include:
A. Complexity of IT Environments
Organizations must establish unified security controls and visibility in order to manage security across hybrid and multi-cloud systems, which can be costly and complex to deploy.
B. Shadow IT and Shadow AI
Unauthorized and unsanctioned applications, systems, tools, practices and processes threaten the very fabric of data privacy and security. Consistent monitoring and governance are core to establishing common grounds of data processing, storage and sharing.
C. Reliance on Legacy Models
Outdated and unsupported legacy infrastructure makes it almost impossible to cater to hyperscale data needs. It also amplifies vulnerabilities, creates compliance gaps and doesn’t integrate with modern systems.
Automate Compliance with Securiti DSPM
Data security management today requires an automated approach that unifies data discovery, classification, access control, and risk remediation across hybrid and multi-cloud environments.
Securiti’s Data Security Posture Management provides holistic insight into the security posture of your data assets, whether on premises, cloud, or spanning multi-cloud environments, and automates your data protection initiatives.
It automatically remediates misconfigurations by continuously assessing, managing, and reporting on data security posture while organizations focus on detecting and remediating risks, ensuring that your sensitive data stays protected at all times.
Request a demo to learn more.
