Data Security for startups
summary
Claims a repeatable startup-ready framework: encrypt all PII across legacy databases and analytics, lock down MySQL behind a proxy with MFA and query logging, and require a JIRA to register PII columns. Uses a UDF that encrypts on ingest into HDFS, Kafka ACLs and Kafka Connect protection, and Apache Ranger ACLs for fine-grained policies. Implements service-to-service token auth via patched HTTP client for decentralized, scalable auth. Reports enabled GDPR readiness, stopped internal plain‑text access, and produced real‑time auditing and containment metrics.
AI-written summary · about
chapters (12)
- 0:00Start
- 1:13Do you know your data?
- 2:41Today's Agenda
- 3:14What is data security?
- 3:51Importance of data security to our organisation
- 5:29Essentials Statistics
- 6:58Point of contention
- 9:16Challenges
- 12:45Databases security
- 17:36Data Platform Solve: Summary
- 20:39Key Metrics
- 20:57Questions???
related talks
31mRings of Security for Big Data in Cloud
26mAnalytics & Data Science with Privacy at its Core
16mWhat if privacy had an API?
40mSecure application design with high data privacy requirements
09mData: Open for Good and Secure by Default
39mdev.privacy: GDPR in a nutshell
35mAppSec Security: The SDLC in the age of agentic
01h 59mDeep Dive Workshop – Data Security and Data Protection
