Connor McDonald explores how Oracle Database security and automation help organizations protect sensitive data, simplify database maintenance, and manage evolving AI security risks. From automated patching with AutoUpgrade to data redaction and Deep Data Security in Oracle AI Database 26ai, discover how Oracle combines database automation with identity-aware access controls to support secure enterprise applications and AI agents.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Connor McDonald about the growing importance of database security as artificial intelligence changes the cybersecurity landscape. Connor explains why AI-powered tools are increasing the urgency of security updates and why organizations should reconsider traditional patch management practices. He discusses Oracle Database release updates, security patches, and AutoUpgrade, which helps database administrators automate patch selection, preparation, installation, and rollback processes while reducing manual effort.

The conversation also explores Oracle Autonomous Database and how managed database services can reduce administrative overhead by automating routine operations, including patching. Connor shares why autonomous database capabilities are particularly valuable for organizations looking to simplify database management while maintaining access to enterprise database functionality.

Franco and Connor then examine security enhancements in Oracle AI Database 26ai, including improvements to Data Redaction that make it easier to protect sensitive information within existing applications. Connor also introduces Deep Data Security, explaining how declarative security policies, data roles, row-level access controls, and integration with external identity systems help organizations manage access to enterprise data.

The episode concludes with a discussion of AI agents and database security, highlighting how Deep Data Security can help trace database interactions through agents and applications back to the originating user. For database administrators, developers, security professionals, and IT leaders, this episode provides practical insights into Oracle Database automation, data protection, identity management, and securing enterprise data in an increasingly AI-driven environment.

Ruiqi Jiang explains how the APEX Graph Visualization Plug-in brings Oracle Graph into Oracle APEX applications for interactive exploration of connected data. Developers can visualize vertices and edges, adjust graph layouts, filter data, customize styling, and connect graph interactions with APEX application processes.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Ruiqi Jiang about Oracle Graph and the APEX Graph Visualization Plug-in, which brings interactive property graph visualization into Oracle APEX applications. Ruiqi explains how Oracle Graph provides built-in capabilities in Oracle Database for representing and querying connected data using property graphs, while the plug-in provides a front-end visualization layer that developers can add as a region within an APEX application.

The conversation explores how developers can use the plug-in to render and interact with vertices and edges, change graph layouts, group or ungroup elements, filter connected data, and customize the appearance of graph visualizations. Ruiqi also discusses ways to provide richer application experiences through node tooltips, interactive page redirects, and AJAX processes.

The episode also looks at the broader developer experience around graph technology, including the GVT library, JavaScript, Visual Studio Code, Python, and Jupyter notebooks. For developers working with Oracle APEX and connected data, the discussion provides an introduction to combining Oracle Graph capabilities with interactive application experiences.

Oracle LiveStacks helps learners explore working, industry-relevant applications before diving into the technologies and architecture behind them. Kevin Lazarz and Matt Howalik explain how LiveStacks combines Oracle LiveLabs with Oracle AI Database 26ai capabilities to connect business outcomes with practical hands-on learning.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Kevin Lazarz and Matt Howalik about LiveStacks on Oracle LiveLabs and a new approach to hands-on technology learning. Instead of beginning with individual product features, LiveStacks provides fully configured applications that let learners experience an industry scenario and its business outcomes before exploring how the underlying architecture works.
Kevin and Matt explain how LiveStacks complements the hundreds of technical workshops already available through Oracle LiveLabs. Learners can begin with a working application, understand the use case, and then explore the technologies that make it possible. The discussion covers examples including AI lakehouse architectures, real-time data ingestion, change data capture, medallion architecture, vector search, JSON, property graphs, and AI capabilities within Oracle AI Database 26ai.
The conversation also explores Select AI, Select AI agents, natural language interaction with data, embedded AI models, and private AI services. Kevin and Matt explain how learners can deploy LiveStacks into their own environments, modify the applications, connect them with AI agents, and then use LiveLabs workshops to understand individual capabilities in greater depth. The result is a practical learning journey that connects real-world applications and business outcomes with the architecture and technologies behind them.

Jason Reinhardt explains how Oracle Live AI Hub uses Autonomous AI Database to connect data across relational databases, files, lakehouses, and clouds for AI-powered analysis and application development. The approach helps organizations work with distributed data where it resides while providing the flexibility to replicate data when performance requirements make that beneficial.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Jason Reinhardt about Oracle Live AI Hub, a solution pattern built on Autonomous AI Database that connects data from multiple sources and makes it available for AI, analytics, and application development. Jason explains how organizations can connect Oracle and non-Oracle databases, relational and unstructured data, files, lakehouse technologies, and data across different clouds without automatically having to move or replicate that data.

The conversation explores how managed connectors can provide access to sources including PostgreSQL, SQL Server, DB2, Snowflake, Databricks, and Apache Iceberg, while organizations can still choose replication technologies when performance requirements call for them. Jason also discusses how the Live AI Hub can support everything from data analysis to polyglot applications, combining relational data, JSON, spatial data, vectors, large language models, and AI agent frameworks through a common database foundation.

Franco and Jason examine how this approach can simplify access to distributed enterprise data while supporting applications built with technologies such as Python and Node.js. They also discuss the role of Autonomous AI Database in providing a managed foundation that can scale from small experiments to larger applications, along with ways developers can get hands-on experience through Oracle Free Tier, developer editions, LiveLabs, and Live Stacks.

Melliyal Annamalai explains why knowledge graphs are becoming a critical foundation for modern AI by providing the context that helps AI agents deliver more accurate and trustworthy results. The conversation explores how property graphs, RDF graphs, vectors, and graph analytics work together to strengthen enterprise AI applications.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Melliyal Annamalai about the growing importance of knowledge graphs in the era of artificial intelligence. As AI systems become more capable, the discussion explores why knowledge graphs are moving beyond their traditional role in analytics to become an essential source of context for AI agents, retrieval systems, and enterprise applications.

Melliyal explains the differences between property graphs and RDF graphs, also known as semantic or knowledge graphs, and describes how each graph model supports different use cases. The conversation examines how knowledge graphs capture business concepts, relationships, and domain expertise in a structured, standards-based way that helps AI systems produce more precise, explainable, and trustworthy outcomes. Real-world examples from fraud detection, financial services, supply chain analysis, and enterprise metadata illustrate how graph technologies continue to evolve alongside AI.

Franco and Melliyal also discuss how vectors and graphs complement one another, combining semantic similarity with explicit relationships to provide richer context for AI. The episode concludes with practical insights into industry ontologies, graph standards, Oracle Graph, and the growing ecosystem of tools and learning resources that are making knowledge graphs increasingly accessible for enterprise AI solutions.

Angelo Joseph explains Oracle's multicloud strategy and how it enables organisations to run Oracle Database services across AWS, Microsoft Azure, and Google Cloud while simplifying operations and procurement. The conversation explores how multicloud deployments improve flexibility, performance, governance, and enterprise AI without requiring customers to change their preferred cloud provider.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Angelo Joseph, head of Cloud Engineering for Oracle Cloud Infrastructure in Australia and New Zealand, about Oracle's multicloud strategy and why it is changing the way organizations deploy enterprise workloads. Angelo explains how Oracle works with major hyperscalers, including Amazon Web Services, Microsoft Azure, and Google Cloud, allowing customers to run Oracle Database services within their preferred cloud environment while maintaining familiar procurement, management, billing, and operational processes.

The conversation explores how Oracle Database and Oracle Exadata services integrate with hyperscaler environments to provide low-latency connectivity, simplified administration, and a consistent enterprise experience. Angelo also discusses Oracle's multicloud commercial model, unified contracts, integrated marketplaces, and the engineering investment required to deliver a seamless customer experience across cloud platforms.

Franco and Angelo also examine how Oracle's approach supports enterprise AI by bringing AI capabilities to the data rather than moving sensitive data between platforms. They discuss operational simplicity, security, autonomous database capabilities, scalability, and the growing adoption of Oracle multicloud across industries including banking, healthcare, telecommunications, retail, and the public sector. This episode provides practical insights for technology leaders evaluating multicloud architectures, enterprise databases, and AI-ready cloud strategies.

Mark Nelson explains how agent memory helps AI systems retain useful context, balance different memory types, and support secure, production-ready AI applications. The discussion explores why governed, durable memory and Oracle AI Database provide a strong foundation for enterprise AI systems.

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Mark Nelson about one of the most important concepts in modern AI development: agent memory. Mark explains why agent memory is much more than chat history and how developers should think about memory as structured, reusable application data rather than a simple transcript of previous conversations.

The discussion introduces six core memory types, including working, semantic, episodic, procedural, relationship, and operational memory, and explains the role each plays in building intelligent AI agents. Mark also examines how popular AI frameworks approach memory, why developers should begin with a clear memory policy instead of a storage technology, and how retrieval, governance, privacy, explainability, and lifecycle management all contribute to trustworthy enterprise AI.

The conversation concludes with a practical discussion of Oracle Agent Memory and Oracle AI Database, showing how vectors, relational data, metadata, graph relationships, and enterprise governance can work together to create durable, searchable, well-scoped, and auditable memory for AI agents. Whether you are building AI applications, experimenting with agent frameworks, or designing enterprise AI architectures, this episode provides a practical framework for understanding how memory enables more capable and reliable AI systems.

Explore practical AI agent strategies for building multi-agent systems with memory, guardrails, observability, and human oversight to improve software development workflows. Hear how these real-world AI learnings can help you build more reliable intelligent systems by listening to the full Digital Impact Radio episode

In this episode of Digital Impact Radio Series 9, Franco Ucci speaks with Mark Nelson about the latest developments in AI agents and the practical lessons he has learned while building production-ready multi-agent systems. Their conversation explores how specialized AI agents collaborate on research, coding, reviews, testing, and fact checking while using memory, observability, and guardrails to improve quality over time. Mark explains how human oversight remains essential for validating outcomes, managing complexity, and maintaining confidence in AI-generated work.

The discussion also covers agent orchestration, model selection, self-hosted language models, development workflows with Visual Studio Code, version control strategies, and considerations for deploying AI agents into production environments. Whether you are exploring AI-assisted software development, intelligent automation, or enterprise AI architecture, this episode offers practical insights into building reliable AI systems that balance automation with governance and continuous improvement.