Nishchai Jayanna Manjula is an experienced Specialist Solutions Architect - Analytics at Amazon Web Services (AWS), with over 15 years of expertise in designing and implementing customer-focused cloud solutions. His core competencies include Big Data, Data Analytics, Machine Learning, and Artificial Intelligence using AWS services. Nishchai has a strong background in Linux administration, database management, data warehousing, and streaming technologies.
Currently serving as a Senior Solutions Architect - Analytics at AWS in Seattle, Washington, Nishchai collaborates with customers to understand their business and technical needs, developing optimized solutions using AWS Cloud and Analytics Services. He actively contributes to AWS forums, blogs, and public speaking events, including AWS Summits and AWS re:Invent, to share best practices and industry insights.
Previously, he worked as a Big Data - Cloud Support Engineer at AWS, assisting clients with Big Data migrations and post-sales support, resolving critical issues related to services such as EMR, Glue, Athena, Redshift, and Kafka. Before AWS, he held key positions at MapR Technologies, Cognizant Technology Solutions, and Wipro Technologies, where he specialized in distributed systems, Big Data platforms, and software development.
Nishchai holds a Bachelor of Engineering in Computer Science from Visvesvaraya Technological University, India. He is certified in AWS Data Analytics - Specialty, AWS Solutions Architecture, and Cloudera Hadoop Development, demonstrating his technical proficiency.
Big Data Analytics, Cloud Computing, Machine Learning, Artificial Intelligence, Data Security, and Streaming Technologies.
In an era where Generative AI is reshaping the digital landscape, organizations face unprecedented challenges in leveraging diverse datasets while ensuring data security and compliance. This presentation explores how Federated Data Marketplaces are emerging as the cornerstone for secure, ethical AI/ML development, enabling organizations to harness the power of Generative AI while maintaining data sovereignty.
We'll deep dive into the critical components of modern federated data marketplaces, including secure enclaves, privacy-preserving computation techniques, and cross-cloud interoperability standards. The session will highlight how these technologies enable organizations to reduce data acquisition costs while improving time-to-insight for AI/ML projects, with special emphasis on Generative AI workloads and their unique requirements.