Legacy systems slow organisations due to scale limits, risk, and cost. In this session, we will walkthrough how enterprises use Archon Data Store, our AI-powered archival platform, to create enterprise-wide data archival strategies for their legacy and modern data. Through use cases from finance, pharma and manufacturing - we will learn intelligent archival techniques that enable organisations to discover their data; align their past, present and future data footprint through decommissioning and migration while enhancing system performance, security and stewardship for their enterprise data.

Securing and derisking AI requires new processes, tools and mindsets. Risks abound internally and externally while regulations take hold. This session outlines frameworks, tools and processes for managing AI trust, risk and security.

Data architects are increasingly tasked with provisioning quality unstructured data to support AI models. However, little has been done to manage unstructured data beyond data security and privacy requirements. This session will look at what it takes to improve the quality of unstructured data and the emerging best practices in this space.

This session will share proven enterprise architecture best practices for augmenting Snowflake with data virtualization to deliver real-time insights. We'll explore how to address latency-sensitive use cases—such as month-end financial reconciliations—while ensuring data security and supporting cloud migration using Denodo. Attendees will learn how the combination of Snowflake and Denodo enables scalable, low-latency analytics across highly customized and distributed data environments.

As enterprises embrace GenAI and intelligent agents, securing sensitive data—like PII, financial records, and IP—while maintaining compliance is crucial. This session explores how Skyflow helps meet modern privacy demands, including India’s DPDP Act, using polymorphic encryption, tokenization, consent management, and fine-grained access controls. See real-world architectures that show how to embed privacy into both legacy and AI-first systems, enabling innovation without compromising security or regulatory compliance.

D&A leaders must develop DataOps as an essential practice to redefine their data management operations. This involves establishing business value before pursuing significant data engineering initiatives, and preventing duplicated efforts undertaken by different teams in managing the common metadata, security and observability of information assets within the data platforms.

The Bank of India is redefining trust through the power of data. Join its Analytics Head as they share how AI, real-time analytics, and predictive insights are transforming security, transparency, and customer experience. Discover how a legacy institution is embracing agility to lead the future of banking.
In addition - see how organizations unlock value with SAS Viya — achieving over 100x performance gains and half the cost in compute and storage costs when modernizing SAS 9 environments. It will explore how Intelligent Decisioning and Generative AI are integrated with data and models to automate decisions and drive stronger business outcomes.