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Accelerating Data Science Initiatives with
Databricks’ SQL Analytics and Privacera’s
Centralized Data Access Governance
Do...
Agenda
▪ Backgrounds
▪ SQL Analytics Overview
▪ Security Challenges
▪ Privacera + SQL Analytics
Integration Overview
▪ Dem...
About the Speaker
▪ Co-founder & CTO, Privacera
▪ Founding member of Apache
Ranger
▪ Strong security partner with
Databric...
Databricks Lakehouse - Persona Driven Approach
● Batch process v/s Real-time
● SQL Analytics simplifies usage of the
Lakeh...
Security and Compliance Challenges
Need consistent policies for the underlying dataset
Persona driven policies
Executives,...
Security v/s Privacy Policies
▪ Preventing unauthorized usage of
systems
▪ Ensuring users don’t see the
incorrect informat...
Governance blind spot
Centralized Auditing and Reporting
● Centralize auditing
● Monitoring data access by classification
● Track usage by Purpo...
Databricks Native Support for Security
Credential Passthrough
SQL Grant/Revoke Cluster Policies
IAM Roles for Cluster
Integration Overview
● Privacera extends Databrick’s native security
● Centrally manage policies for all Databricks worklo...
Privacera - Traditional Databricks Workspaces Support
Fine Grained Access Control
SQL - Database, Table, Column
SQL - Dyna...
Databricks/Privacera - Ranger Plugin Architecture
SQL Analytics - Databricks + Privacera
Seamless integration
No Privacera deployment
No plugins and no init scripts
Privace...
Privacera + SQL
Analytics Key Benefits
Privacera’s data access governance
platform seamlessly integrates with
SQL Analytic...
Demo
Thank you!
Contact Me
SOCIAL
LinkedIn: https://www.linkedin.com/in/donboscodurai/
Sign up for a free 30-day trial of PrivaceraCloud a...
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Accelerate Data Science Initiatives: Databricks & Privacera

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Accelerating Data Science Initiatives with Databricks’ Rapid SQL Analytics and Privacera’s Centralized Data Access Governance.



Databricks’ SQL Analytics helps data teams consolidate and simplify their data architectures. With SQL Analytics, data teams can perform BI and SQL workloads on the same multi-cloud lakehouse architecture enabling data scientists to perform advanced analytics on unstructured and large-scale data. This session will explore how Privacera’s advanced security, privacy, and governance capabilities seamlessly integrate with Databricks’ unified SQL Analytics approach to provide single pane visibility of data analytics from a centralized location. Attendees will learn how to:



Rapidly access data to run high-fidelity analytics
Implement a fully secure solution that ensures productivity, while controlling data access at fine-grained levels (row, column, and file)
Easily enable consistent access policies across all systems and applications
Support true data transparency across enterprises
Comply with stringent industry and privacy regulations like GDPR, LGPD, HIPAA, CCPA, PCI DSS, RTBF, and more with rich auditing and reporting

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Accelerate Data Science Initiatives: Databricks & Privacera

  1. 1. Accelerating Data Science Initiatives with Databricks’ SQL Analytics and Privacera’s Centralized Data Access Governance Don Bosco Durai Co-Founder and CTO, Privacera
  2. 2. Agenda ▪ Backgrounds ▪ SQL Analytics Overview ▪ Security Challenges ▪ Privacera + SQL Analytics Integration Overview ▪ Demo ▪ Key Benefits
  3. 3. About the Speaker ▪ Co-founder & CTO, Privacera ▪ Founding member of Apache Ranger ▪ Strong security partner with Databricks
  4. 4. Databricks Lakehouse - Persona Driven Approach ● Batch process v/s Real-time ● SQL Analytics simplifies usage of the Lakehouse for Business users ● Data Scientist and Architects can continue using ML Workflow Spark Clusters ● Customizable security policies for different use cases
  5. 5. Security and Compliance Challenges Need consistent policies for the underlying dataset Persona driven policies Executives, Data Analyst, Data Scientist, Data Wranglers, etc. Managing access permissions for different Personas Can everyone run grant/revoke SQL commands? What IAM role should be attached to the cluster? Who can create a new cluster?
  6. 6. Security v/s Privacy Policies ▪ Preventing unauthorized usage of systems ▪ Ensuring users don’t see the incorrect information ▪ Creating boundaries to enforce right action of the system • “Data privacy may be defined as the authorized, fair, and legitimate processing of personal information” • Consent rights • Do not share Privacy Security
  7. 7. Governance blind spot
  8. 8. Centralized Auditing and Reporting ● Centralize auditing ● Monitoring data access by classification ● Track usage by Purpose ● Generate attestation reports
  9. 9. Databricks Native Support for Security Credential Passthrough SQL Grant/Revoke Cluster Policies IAM Roles for Cluster
  10. 10. Integration Overview ● Privacera extends Databrick’s native security ● Centrally manage policies for all Databricks workloads ● Consistent policies between Databricks SQL Analytics and Python/SQL Workspaces ● Centralized collection of Audit Records ● Built on top of Apache Ranger ○ High Scalable ○ Support for multiple services and Clouds
  11. 11. Privacera - Traditional Databricks Workspaces Support Fine Grained Access Control SQL - Database, Table, Column SQL - Dynamic Row Level Filtering SQL - Dynamic Column Masking S3/ADLS file level access control Attribute Based Access Policies Role Based Access Policies Tag Based Policies S3/ADLS file level access control Attribute Based Access Policies Role Based Access Policies Tag Based Policies • Scala Cluster • Python/SQL Cluster
  12. 12. Databricks/Privacera - Ranger Plugin Architecture
  13. 13. SQL Analytics - Databricks + Privacera Seamless integration No Privacera deployment No plugins and no init scripts Privacera’s Policy Sync integration design Security features identical to Databricks SQL Cluster
  14. 14. Privacera + SQL Analytics Key Benefits Privacera’s data access governance platform seamlessly integrates with SQL Analytics to provide: ● Fine-grained access control at row- and column- levels with dynamic masking ● Single-pane visibility of data across multiple cloud services in SQL Analytics ● Precise data usage with real-time monitoring, logging, and audit trails ● Compliance with industry and privacy regulations like GDPR, CCPA, HIPAA, LGPD
  15. 15. Demo
  16. 16. Thank you!
  17. 17. Contact Me SOCIAL LinkedIn: https://www.linkedin.com/in/donboscodurai/ Sign up for a free 30-day trial of PrivaceraCloud at privacera.com/try-privaceracloud

Accelerating Data Science Initiatives with Databricks’ Rapid SQL Analytics and Privacera’s Centralized Data Access Governance. Databricks’ SQL Analytics helps data teams consolidate and simplify their data architectures. With SQL Analytics, data teams can perform BI and SQL workloads on the same multi-cloud lakehouse architecture enabling data scientists to perform advanced analytics on unstructured and large-scale data. This session will explore how Privacera’s advanced security, privacy, and governance capabilities seamlessly integrate with Databricks’ unified SQL Analytics approach to provide single pane visibility of data analytics from a centralized location. Attendees will learn how to: Rapidly access data to run high-fidelity analytics Implement a fully secure solution that ensures productivity, while controlling data access at fine-grained levels (row, column, and file) Easily enable consistent access policies across all systems and applications Support true data transparency across enterprises Comply with stringent industry and privacy regulations like GDPR, LGPD, HIPAA, CCPA, PCI DSS, RTBF, and more with rich auditing and reporting

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