How DPDP Act will define data privacy in the digital-first world

In CIO’s 2024 Security Priorities study, 40% of tech leaders said one of their key priorities is strengthening the protection of confidential data. Cohesive, structured data is the fodder for sophisticated mathematical models that generates insights and recommendations for organizations to take decisions across the board, from operations to market trends. But with big data comes big responsibility, and in a digital-centric world, data is coveted by many players.

Protecting data from bad actors

In an era where cyber threats are increasingly sophisticated, organizations must adopt a proactive security strategy to safeguard sensitive data. Kapil Madaan, CISO and DPO, Max Healthcare says, “A comprehensive Data Protection Framework ensures resilience against breaches by integrating encryption, strict access controls, and advanced threat detection technologies. A Multi-Layered Security Strategy and ML algorithms enhance protection by utilizing AI-driven threat detection to monitor network anomalies and identify potential risks in real time.”

Kiran Belsekar, Executive VP – CISO and IT Governance, Bandhan Life reveals that ensuring protection and encryption of user data involves defence in depth with multiple layers of security. “Using Zero Trust Architecture (ZTA), we rely on continuous authentication, least privilege access, and micro-segmentation to limit data exposure.” He also stands by DLP protocol, which monitors and restricts unauthorized data transfers, and prevents accidental exposure via email, cloud storage, or USB devices.

Vishwas Pitre, CISO and DPO Zensar Technologies also highlights, “Configuring multi-factor authentication with FIDO-2 verification to access sensitive systems and data enhances the second level of authentication and reduces the risk of unauthorized access.”

Kapil summarises, “By integrating encryption, Zero Trust policies, and AI-powered threat intelligence, enterprises can create a robust cybersecurity ecosystem that not only defends against evolving threats but also fosters business continuity and regulatory compliance”.

In (clean) data we trust

While data is invaluable, all data is not created equal. Error-filled, incomplete or junk data can make costly analytics’ efforts unusable for organizations.

Ravinder Arora elucidates the process to render data legible. “Our data governance frameworks define clear standards for data quality, accuracy, and relevance to collect usable data that drives meaningful insights. We also leverage automated data classification, role-based access controls (RBAC) and regular audits ensure only high-quality data is stored and analyzed. By aligning data collection with business objectives and compliance standards and regulations like ISO 27001, GDPR and DPDPA, we ensure that only structured, actionable data fuels analytics, leading to better decision-making and operational efficiency.”

Kiran Belsekar makes a case for data structures. “Use Master Data Management (MDM) to create a single source of truth for critical business entities. Additionally, standardize naming conventions and ensure consistency across databases.” In this regard, data governance & quality metrics can be employed, defining key data quality dimensions such as accuracy, completeness, consistency, and timeliness.

On Human Error

Organizations must recognize that employees are both their greatest asset and their biggest vulnerability when it comes to cybersecurity. Vishwas Pitre preaches the route of training and simulated threats, with employees being made aware of data security best practices, phishing attempts to test vigilance, and compliance with regulations like GDPR or the upcoming DPDP Act. Kapil Madaan adds that regular cybersecurity training focusing on critical topics such as password security, safe browsing habits, and emerging cyber threats, ensuring a security-conscious workforce.

He continues, “Beyond traditional training methods, interactive awareness programs—such as cybersecurity quizzes and hands-on workshops—create a dynamic learning environment that make security education more impactful. This culture continuous learning and vigilance can help transform the workforce into a strong line of defence against cyber threats, ensuring data security and operational resilience.”

Taking AI to new heights with data

Rich, usable data will empower organizations to leverage emerging technologies like Artificial Intelligence to augment their business across the board, from operations to customer experience.

Kapil Madaan highlights the endless possibilities of privacy solutions that AI heralds. “Organizations are turning to AI-powered technologies to proactively detect and mitigate cyber threats in real time. AI-driven SIEM systems and User and Entity Behaviour Analytics (UEBA) enable continuous monitoring and automated threat response, significantly reducing risks, as do (EDR) solutions. Beyond cybersecurity, AI is also optimizing operations through intelligent automation, NLP and RPA.”

Vishwas Pitre heralds how AI will help analyse customer behaviour and preferences, enabling personalized experiences and targeted marketing campaigns. By integrating these cutting-edge tools, organizations can build a proactive, AI-driven security and operations framework, ensuring agility, efficiency, and protection in an increasingly digital world.