Secure Data Management for AI Implementation
1hIntermediate2025-04-02
Authors
Dr. Brandeis Marshall
Course details
At the core of many businesses is data, which requires organization, security, mining, and analysis. The operating logistics of data stewardship, data security, data, and database administration can become complicated and overwhelming for organizations that are executing without a stable roadmap. This course aims to introduce the security of business enterprise infrastructure and operating needs. Instructor Brandeis Marshall examines advanced design techniques and physical issues relating to enterprise-wide data management. Learn about advanced design concepts, enhanced modeling and constructs, objects and unstructured and semi-structured data in databases, implementation of an enterprise data architecture, and data quality and stewardship. Join Brandeis as she shares database security best practices while making them relatable and accessible.
Learning objectives
Define key components of database security.
Understand under which conditions to enforce granular control mechanisms.
Determine when to secure database-to-database communications.
Identify multi-level security in database systems.
Learning objectives
Define key components of database security.
Understand under which conditions to enforce granular control mechanisms.
Determine when to secure database-to-database communications.
Identify multi-level security in database systems.
Skills covered
MySQLData Resource ManagementData PrivacyArtificial Intelligence FoundationsDatabase ManagementArtificial Intelligence (AI)Data ScienceOpen SourceOne-Off
Concepts
0. Introduction
- 01 - Protecting Data Communications in AI Systems
1. Data Security Fundamentals
- 02 - Database security overview
- 03 - What's security architecture
- 04 - Identifying database threats and vulnerabilities
- 05 - Protecting against malware
2. Granular Access Control
- 06 - Database control language overview
- 07 - Authentication schemes
- 08 - Authorization methods
- 09 - Encryption practices
3. Securing database-to-database communications
- 10 - Monitoring and protecting data sources
- 11 - Replication - to-dos and to-don'ts
- 12 - Transfer Issues from applications to the cloud
- 13 - Security auditing
4. Multi-level security in database systems
- 14 - Vulnerability assessment and patch management
- 15 - Reinforcing and enforcing application security
- 16 - Reinforcing and enforcing security management
5. Case study - Use AI to Secure Your Data
- 17 - Case study setup
- 18 - Case study walkthrough
Conclusion
- 19 - Next steps