Complying with GDPR is a critical obligation for businesses handling user data, but it’s no secret that it consumes significant engineering time. Reviewing systems, implementing safeguards, updating documentation, and managing user data requests are immensely time-intensive. However, with the right strategies and tools, businesses can significantly reduce this overhead while ensuring compliance.
This post explores practical steps to reduce the engineering time spent on GDPR compliance and explains how automation plays a crucial role. If you’re striving to save engineering hours without sacrificing compliance, keep reading.
Breaking Down GDPR Challenges that Consume Engineering Time
GDPR requirements are demanding, but understanding which tasks disproportionately drain engineering resources helps you attack inefficiencies at the source.
- Data Mapping and Inventory:
Identifying where personal data resides across systems involves combing through databases, APIs, and codebases. This process often requires hands-on discovery from engineering teams. - Responding to Data Subject Requests (DSRs):
Handling access, deletion, and portability requests is a time-sink when done manually. Engineers might have to query systems, write scripts, and validate data retrieval processes. - Audit and Documentation Updates:
GDPR demands meticulous documentation around data processing activities. Engineers often end up shouldering the load of ensuring records match automated behavior. - Privacy by Design Implementation:
Introducing privacy-friendly defaults and ensuring proper data anonymization requires ongoing engineering bandwidth. Retrofitting legacy systems can eat into sprint plans. - Monitoring and Reporting Compliance:
Real-time monitoring of GDPR compliance is an added layer of complexity, requiring engineers to implement logging, alerting, and periodic system reviews.
Streamlined Solutions to Save Hours
Here’s a breakdown of actionable methods to lessen the engineering effort spent on GDPR compliance.
Automate Data Mapping and Discovery
Automation platforms that scan your infrastructure to locate and classify personal data save engineering teams hours of manual investigation. By maintaining an always-updated view of where data resides, you prevent the time-wasting cycle of rediscovery.
Adopt Centralized DSR Portals
Building a robust system for Data Subject Requests allows non-technical teams to self-serve. By abstracting access to approved endpoints and integrating automated workflows, most requests can be processed without coding or engineering intervention.