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Unlock DPDPA Compliance with the Power of Automated Data Mapping

April 7, 2025

In today’s digital economy, data is an invaluable asset driving business growth and operational efficiency across industries. With the widespread adoption of cloud computing, hybrid IT environments, and increasing digital transformation, organizations now manage vast volumes of personal and sensitive data across distributed platforms. This shift has made data management significantly more complex and challenging.

Simultaneously, governments around the world have begun enacting rigorous data protection regulations to ensure responsible handling of personal data. One such landmark legislation is India’s Digital Personal Data Protection Act (DPDPA), 2023— which imposes stringent requirements on how personal data of Indian citizens is collected, stored, processed, and transferred. With steep penalties of up to ₹250 crore (~$30 million) for non-compliance, organizations operating in India must place Data Mapping at the heart of their privacy and data governance strategies.

However, cloud-based data mapping comes with its own unique challenges:

  • Data Sprawl Across Multi-Cloud and Hybrid Environments: Enterprises rely on platforms like AWS, Azure, Google Cloud, and SaaS apps—making it difficult to trace and control data. Cloud adoption among enterprise organizations is over 94%, and shows no signs of going down.
  • Lack of Visibility Over Sensitive Data: Unstructured data such as contracts, chats, and emails often contain personal data that remains hidden.
  • Compliance Risks: Regulatory mandates like localization and consent make real-time visibility and control over data essential.
  • Incident Response Complexity: The DPDPA requires timely breach reporting, pushing organizations to adopt real-time monitoring and discovery tools.

This blog post provides a comprehensive roadmap for organizations to:

  • Understand why automated data mapping is vital in modern cloud environments
  • Align data protection strategies with compliance obligations under DPDPA and other similar privacy regulations
  • Tackle technical and regulatory hurdles to data visibility
  • Implement proven best practices to strengthen governance, security, and privacy readiness
  • Leverage Exterro’s AI-powered Automated Data Mapping solution to automate classification, mapping, risk analysis, and compliance reporting in real time

Introduction: The Growing Need for Data Discovery in the Cloud

Cloud Adoption and the Changing Data Landscape

Cloud technologies have revolutionized IT operations, transitioning enterprises from legacy systems to hybrid and multi-cloud ecosystems. This shift offers substantial benefits:

  • Scalability: Dynamically scale computing and storage based on business demands.
  • Cost Efficiency: Reduce capital expenditures and infrastructure overhead.
  • Agility and Innovation: Accelerate deployment of apps and services, while adopting AI and analytics seamlessly.

Yet this flexibility also introduces significant risk. With data scattered across platforms and lacking centralized control, cloud environments create governance and security blind spots that traditional tools cannot address.

The Challenges of Cloud Data Management

Cloud-first architectures demand a new approach to managing sensitive and personal data. Organizations face several key challenges:

1.      Unstructured Data Proliferation
Over 80% of enterprise data is unstructured and resides in emails, documents, chats, logs, and SaaS apps. This data is rarely labeled or classified, making it difficult to locate, assess, or secure.

2.      Multi-Cloud and Hybrid Fragmentation
Data is often distributed across AWS, Azure, GCP, private clouds, and legacy on-premises systems (with 98% of enterprises using or planning to use two or more cloud providers). Without unified visibility, organizations cannot track where personal data resides or moves.

3.      Shadow IT and Data Sprawl
Employees use unauthorized tools or store sensitive files in personal cloud accounts, creating unknown data silos that escape governance and introduce compliance blind spots.

4.      Security and Access Control Gaps
Inadequate access controls and privilege mismanagement increase the risk of internal data leaks. Organizations need to enforce least privilege principles, role-based access control (RBAC), and multifactor authentication (MFA).

5.      Regulatory Complexity
The DPDPA requires organizations to monitor personal data flows, obtain valid consent, ensure local storage, fulfill data subject requests, and report breaches—all of which demand full lifecycle visibility.

Why Data Discovery is Essential for Regulatory Compliance

You can’t protect what you don’t know exists. Data mapping is the foundation upon which all other security measures are built. It is the process of automated data scanning and detecting, cataloging, and classifying personal and sensitive data across an enterprise’s IT landscape. It should be at the forefront of every information security professional’s mind.  

This capability is foundational to:

  • Regulatory Compliance: Meeting obligations under the DPDPA, GDPR, and global data protection laws
  • Risk Management: Identifying unauthorized data access, sensitive data sprawl, and security threats
  • Data Security: Enforcing encryption, access control, and secure retention policies
  • Incident Response: Rapidly locating compromised data and notifying affected stakeholders
  • Data Minimization - Allowing organizations to identify and eliminate unnecessary data, reducing the attack surface and simplifying data management.

With the DPDPA's enforcement deadlines imminent, organizations must adopt advanced, automated, and AI-powered data mapping solutions to ensure continuous compliance and mitigate risk. 

Understanding the DPDPA and its Impact on Cloud Data

Enacted in 2023, the Digital Personal Data Protection Act (DPDPA) introduces significant changes to how personal data must be managed in India. It prioritizes individual privacy rights while mandating responsible data governance.

Key DPDPA Provisions and Relevance to Data Discovery

Provision

Impact on Cloud-Based Data Discovery

Explicit Consent

Organizations must trace where data obtained via valid consent is processed and stored.

Data Localization & Cross-Border Transfers

Personal data cannot be transferred to restricted destinations—requiring geographic-level visibility.

Data Principal Rights

Companies must identify and act on requests for access, correction, and deletion of personal data.

Breach Notification

Security incidents involving personal data must be detected and reported swiftly to regulators and individuals.

Non-Compliance Penalties

Fines up to ₹250 crore (~$30 million)—data discovery accuracy is essential to avoid violations.

 How to Prepare for Compliance

  • Deploy AI-driven data mapping platforms to classify and monitor personal data
  • Map data flows across cloud, SaaS, and legacy environments
  • Automate access controls and real-time breach detection
  • Establish audit-readiness through accurate data tracking and reporting

Challenges in Data Discovery Under India’s Privacy Law

Despite the urgency, implementing effective cloud-based data discovery is far from straightforward. Organizations face several practical and regulatory challenges:

1. Complexity of Multi-Cloud and Hybrid Infrastructures

Modern enterprises rarely rely on a single cloud provider. Instead, they operate in multi-cloud or hybrid cloud ecosystems, where data is distributed across:

  • Public clouds
  • Private clouds (for regulated or high-sensitivity data)
  • On-premise infrastructure (legacy systems) 
  •  SaaS apps

This results in:

  • Fragmented data silos with no centralized view
  • Poor classification of personal data
  • Duplicate or conflicting records
  • Inability to trace data lineage across platforms

Example: A financial firm may store “Know Your Customer” (KYC) data on AWS, transaction records on-prem, and campaign data in Google Cloud. Without a unified mapping tool, they cannot track all personal data, risking DPDPA violations.

2. Explosive Growth of Unstructured and Shadow Data

Unstructured data accounts for the majority of enterprise content. 80% to 90% of global data exists in the form of unstructured data. The unstructured data are wildly difficult to search, analyze, and catalog. It exists in:

  • Emails, PDFs, spreadsheets
  • Messaging tools (Teams, Slack)
  • Logs, error files, reports
  • Employee-managed SaaS or personal cloud apps

Without control over this data:

  • Organizations cannot locate PII and other sensitive information
  • Unauthorized storage locations proliferate
  • Data subject requests become infeasible

3. Data Localization and Cross-Border Data Transfer Restrictions

The DPDPA emphasizes data localization:

Challenge: Without real-time mapping of data location, cross-border violations may occur unknowingly.

4. Real-Time Compliance with Data Subject Rights Requests

The law grants Indian citizens the right to:

  • Access their data
  • Correct inaccuracies
  • Request deletion under the “Right to be Forgotten”

To comply, organizations must:

  • Find and retrieve personal data quickly
  • Validate and process correction/deletion securely
  • Keep detailed logs of actions for accountability

5. Incident Response and Breach Notification Complexity

Under DPDPA, breaches must be reported to:

Challenges include:

  • Quickly identifying affected data and individuals
  • Knowing whether compromised data involves Indian citizens
  • Generating accurate, regulator-ready reports within deadlines

 

Best Practices for Cloud-Based Data Discovery and Privacy Compliance

Organizations should adopt the following best practices to align with the DPDPA:

1. Deploy AI-Powered Data Mapping Solutions

  • Use machine learning to scan and tag sensitive data
  • Automate discovery across cloud, on-prem, and hybrid environments
  • Enable continuous monitoring for policy violations

2. Implement a Comprehensive Data Governance Framework

  • Define policies for data retention, deletion, and access
  • Assign roles for data stewardship, privacy, and compliance
  • Schedule regular audits to ensure enforcement

3. Gain Visibility into Data Access and Permissions

  • Monitor user access to sensitive data
  • Enforce least privilege with RBAC
  • Review access logs and detect abnormal behavior

4. Strengthen Cloud Security Controls

  • Encrypt data at rest and in transit
  •  Implement MFA and endpoint protection
  • Integrate SIEM tools for threat intelligence

How Exterro’s Automated Data Mapping Solution Enables DPDPA Compliance

Exterro delivers an intelligent, automated platform to help organizations meet DPDPA obligations. Key capabilities include:

1.      Personal and Sensitive Data Discovery

  • Uses AI to detect and classify PII, SPI, and regulated data types
  • Covers structured (databases), unstructured (documents), and semi-structured sources
  • Continuously updates discovery results with real-time data scanning

2.      Automated Data Mapping & Real-Time Visibility into Data Flows

  • Creates dynamic data flow diagrams
  • Detects unauthorized cross-border transfers
  • Identifies dark and shadow data in forgotten repositories

3.      Data Subject Access Request Automation

 4. ROT Data Detection and Minimization

5. Real-Time Risk Scoring and Compliance Monitoring

  • Assigns sensitivity levels to datasets
  • Alerts users about risky configurations or storage violations
  • Produces audit-ready compliance reports

6. Breach Detection and Response

  • Monitors for data exfiltration and suspicious activity
  • Pinpoints compromised datasets instantly
  • Generates automated breach reports for regulators

 7. Seamless Integration and In-Place Analysis

  • Connects with AWS, Azure, GCP, M365, Salesforce, and more
  • Analyzes data without moving it from its source
  • Reduces the risk of data duplication or leaks

Why Exterro?

Exterro is a trusted leader in data privacy, digital forensics, and regulatory compliance, helping enterprises worldwide simplify data governance, improve security, and reduce compliance risks.

  • Enterprise-Grade Scalability: Manage petabytes of data across global infrastructure
  • Security-First Approach: Native environment scanning prevents exposure
  • Rapid ROI: Eliminate manual discovery and reduce compliance costs
  • Trusted by Global Enterprises: Proven results in privacy, DFIR, and legal compliance

Conclusion: The Future of Cloud-Based Data Protection in India

India’s DPDPA is a bold step forward in digital privacy enforcement. To comply confidently, organizations must adopt robust, automated, and cloud-native data governance practices.

Key Takeaways

  • Data mapping is essential for meeting DPDPA, GDPR, and global mandates
  • Manual processes cannot scale to meet real-time compliance demands
  • Exterro enables organizations to visualize, secure, and manage sensitive data with confidence

Next Steps for Organizations

Learn how Exterro Data Privacy, Security, and Governance solutions can streamline DPDPA compliance and secure your cloud data. 

 

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