Webinar: Ingest, transform, and pre-process your unstructured data for AI with IBM
Webinar live date: May 14, 2025
Webinar live time: 11 AM EDT | 5 PM CEST
Join this Chat with the Lab session to discover how IBM is extending our data integration framework—traditionally used for structured data—to unstructured data, with new capabilities for ingestion, transformation, and vectorization to power RAG use cases.
In the era of agentic AI, leveraging enterprise data is more critical than ever—yet only about 1% is used in AI applications. This is largely due to the rapid growth of unstructured data, which now accounts for 90% of enterprise data—a vast, untapped goldmine. Extracting value from it remains challenging, often requiring manual work, custom code, and third-party tools, making the process slow and hard to scale. Join us for this webinar to explore how IBM’s new support for Unstructured Data Integration.
Key takeaways:
— Collect diverse unstructured data types from a variety of disparate sources.
— Leverage pre-built functional and quality operators to transform raw unstructured data into AI-ready data from a low/no code UI with drag and drop functionality.
— Populate supported vector databases with embeddings to be used for RAG use cases.
Speakers:
— Sophie Jin, Product Manager, IBM Data Integration
— Caroline Garay, Product Marketing Manager, IBM DataStage & Unstructured data
— Jojo Joseph, Product Architect, IBM Data and Al
— Deepa Yarangatta Ramamurthy, Senior Software Engineer, IBM
Webinar live date: May 14, 2025
Webinar live time: 11 AM EDT | 5 PM CEST
Join this Chat with the Lab session to discover how IBM is extending our data integration framework—traditionally used for structured data—to unstructured data, with new capabilities for ingestion, transformation, and vectorization to power RAG use cases.
In the era of agentic AI, leveraging enterprise data is more critical than ever—yet only about 1% is used in AI applications. This is largely due to the rapid growth of unstructured data, which now accounts for 90% of enterprise data—a vast, untapped goldmine. Extracting value from it remains challenging, often requiring manual work, custom code, and third-party tools, making the process slow and hard to scale. Join us for this webinar to explore how IBM’s new support for Unstructured Data Integration.
Key takeaways:
— Collect diverse unstructured data types from a variety of disparate sources.
— Leverage pre-built functional and quality operators to transform raw unstructured data into AI-ready data from a low/no code UI with drag and drop functionality.
— Populate supported vector databases with embeddings to be used for RAG use cases.
Speakers:
— Sophie Jin, Product Manager, IBM Data Integration
— Caroline Garay, Product Marketing Manager, IBM DataStage & Unstructured data
— Jojo Joseph, Product Architect, IBM Data and Al
— Deepa Yarangatta Ramamurthy, Senior Software Engineer, IBM