Data Architect · Softech International Resources Inc
Most organisations rush to deploy AI tools before their data foundation is ready to support them. The result is predictable poor adoption, unreliable outputs, data security incidents, and AI investments that fail to deliver measurable returns. The problem is rarely the AI tool itself. It is almost always the data infrastructure beneath it.nIn this talk, Rajesh Kumar a Senior Data Architect with 12+ years of enterprise data integration experience shares a practical framework for building data infrastructure that makes AI work at scale. Drawing on real-world delivery experience across multiple industries including financial services, manufacturing, supply chain, and healthcare, he will walk through the foundational decisions that determine whether an organisation's AI programme succeeds or stalls.nAttendees will learn how to design scalable ETL/ELT pipelines that feed AI workloads reliably, how to implement data quality frameworks that ensure AI systems receive clean, governed, and trustworthy data, and how to architect cloud data warehouses on platforms like Snowflake and AWS that scale with growing AI demand.nThe session will also cover responsible AI data practices including how organizations can prevent sensitive data from entering AI systems and how to measure AI adoption through analytics rather than assumption.nThis is a practitioner-led session grounded in real deployments not theory. Whether you are a data engineer, architect, or technology leader evaluating your organization's AI readiness, you will leave with a clear, actionable framework you can apply immediately.