Organizations across all industries face unprecedented challenges in securing their most valuable assets: their data. While the ability to identify and visualize data risks has improved dramatically with the emergence of Data Security Posture Management (DSPM) solutions, mere visibility is no longer sufficient. To truly protect high-value data assets, organizations must shift their data security strategy “left” – focusing on actionability rather than just detection.

The Visibility Problem

Traditional approaches to data security have emphasized finding sensitive data and reporting on potential risks. This visibility-centric approach has yielded important benefits:

  • Increased awareness of where sensitive data resides
  • Better understanding of potential compliance issues
  • Improved reporting for audits and regulatory requirements

However, visibility alone creates several challenges:

  • Alert Fatigue: Security teams become overwhelmed with findings they cannot act upon
  • Responsibility Gaps: SOC analysts often lack access to remediate issues in databases and applications
  • Resource Constraints: Limited security staff cannot manually address the volume of identified risks
  • Compliance Without Protection: Organizations achieve technical compliance without meaningful risk reduction

The Shift-Left Approach to Data Security

Shifting left in data security means integrating actionability directly into your discovery and classification processes. Rather than treating detection and remediation as separate workflows, a shift-left approach fuses them together, enabling immediate action on discovered risks.

This approach transforms data security from a reactive, report-generating exercise into a proactive, risk-reducing function that delivers tangible security benefits.

Key Elements of an Action-Oriented Data Security Strategy

1. Comprehensive Data Discovery and Classification

Before you can act, you need to know what you’re acting upon. This requires:

  • Complete Data Discovery: Broad coverage across cloud, SaaS, and on-premises environments
  • Advanced Data Classification: Using AI, pattern matching, and exact data matching to classify, categorize, and catalog all sensitive, critical, personal, and regulated data—including AI training data
  • Continuous Monitoring: Detecting changes in data positioning and sensitivity

2. Integrated Risk Detection and Remediation

The most critical shift is connecting discovery directly to remediation capabilities:

  • Automated workflows that trigger immediate actions based on risk signals
  • Delegated remediation to empower data owners—such as Dev and App Dev teams—to address issues directly
  • Integration with existing security tools via SOAR blueprints and APIs

3. Diverse Remediation Actions

Different risks require different responses. A comprehensive action portfolio includes:

  • Data Access Governance: Detecting and revoking excessive permissions
  • Data Lifecycle Management: Identifying and eliminating duplicate, stale, and orphaned data
  • Protection Mechanisms: Implementing masking, tokenization, redaction, and encryption
  • Activity Monitoring: Detecting and responding to suspicious access patterns

4. Decentralized Responsibility Model

Security teams cannot address all data risks alone. An effective shift-left strategy ensures that remediation responsibility is distributed efficiently across the organization:

  • Delegating to Data Owners: Security teams can assign remediation tasks to application developers, DevOps, and business owners responsible for specific data sources. This is critical for addressing risks like exposed secrets, hardcoded keys, and misconfigured access settings in development environments.
  • Contextual Information & Guided Remediation: BigID provides data owners with clear risk context, remediation recommendations, and automated workflows to act swiftly and correctly.
  • Streamlined Accountability: Security teams retain oversight through audit trails, ensuring all remediation actions are tracked and verified.

How BigID Enables Actionable Data Security

BigID is uniquely positioned to help organizations shift their data security strategy left by enabling actionability at every stage of the security lifecycle. Here’s how BigID excels:

  • Complete Data Discovery: AI-driven discovery provides deep visibility into structured and unstructured data across cloud, SaaS, and on-premises environments.
  • Advanced Data Classification: BigID classifies, categorizes, and catalogs all sensitive, critical, personal, and regulated data—including AI training data—to improve accuracy and risk assessment.
  • Risk-Aware Automation: BigID’s DSPM capabilities go beyond visibility by integrating automated risk detection and remediation workflows, reducing the burden on security teams.
  • Integrated Remediation Actions: Organizations can automate remediation processes such as policy enforcement, access revocation, and data minimization directly from the BigID platform.
  • Seamless Integrations: BigID connects with SIEM, SOAR, ITSM, and security tools, ensuring that risk insights lead to real-time action without disrupting existing workflows.
  • Empowered Data Ownership: BigID enables security teams to delegate remediation tasks to data owners- such as Dev and App Dev teams responsible for databases and application data—while maintaining oversight, streamlining response, and accountability.

Benefits of Shifting Left

Organizations that successfully shift their data security strategy toward actionability realize several benefits:

  • Reduced Risk Exposure Time: Immediate action shortens the window during which sensitive data remains vulnerable
  • Improved Resource Utilization: Security teams focus on high-priority issues rather than managing an endless backlog
  • Enhanced Compliance Posture: Actions create verifiable evidence of risk mitigation for auditors
  • Scalable Security Operations: Automated and delegated remediation enables security functions to scale with data growth

Overcoming Implementation Challenges

Shifting left requires addressing several common challenges:

Challenge Solution
Limited visibility across data sources Deploy a platform with broad cloud, SaaS, and on-premises coverage.
High false positives in risk detection Leverage AI-driven classification and exact data matching.
Integration with existing security tools Use solutions with pre-built connectors for SIEM, SOAR, and ITSM platforms.
Resistance to shared responsibility Provide contextual risk insights and structured workflows for non-security teams.

 

Conclusion

As data continues to proliferate across diverse environments, organizations can no longer afford to treat data security as a visibility exercise. By shifting left and embedding actionability into the core of data security strategy, organizations can move beyond knowing about risks to actively reducing them.

The most advanced organizations are already making this transition, evolving from DSPM to comprehensive Data Security Platforms (DSP) that combine discovery, classification, risk analysis, and remediation into unified solutions. This approach doesn’t just secure data more effectively—it transforms data security from a cost center into a business enabler that protects the crown jewels that power digital innovation.

In a landscape where data is both an organization’s greatest asset and its greatest liability, the ability to act swiftly and effectively on data risks has become the new standard for security excellence.

Want to learn more about how we’re helping organizations shift left? Schedule a 1:1 with one of our DSPM experts today!