Kafka is proving its worthy as a persistent data repository. Near Real Time (NRT) analytics access to dynamic transactional data has been a boon for Data Scientists in performing advanced analytics, ML and AI operations on transactional data in NRT. Unfortunately, Kafka adoption is restricted whenever sensitive or regulated data is involved. Discover how a data-centric security & privacy approach for Confluent and KSQL has enabled companies to remove this barrier to Kafka adoption. Transparently augmenting Kafka with data security features and functionality like Data Discovery, Purpose Based Access Control (PBAC), Accountability, Monitoring and Alerting and Auditing for all data access is the first step. Enhancing data protection with platform agnostic Encryption, Dynamic Masking, PBAC, Privacy Compliance for HIPAA, CCPA, GDPR by enforcing RTBF, Consent/Preference Management, Geo-Fencing and Hold Your Own Key (HYOK) - segregating data encryption keys from the compute platform completes the transition of Kafka to a truly secure platform, when all access to sensitive or regulated data by any Users or Administrators is controlled and audited. Data protection and access controls must be centrally managed and abstracted from the Producer and Consumer processes. Only then will Kafka be fully accepted for processing sensitive or regulated data.