From Air Quality to Aircraft and Automobiles, Data Is Everywhere

Session Track: Knowledge Graphs

Session Time: 11:00 pm - 11:15 pm November 6

Session description

Tim Spann explores how Apache NiFi can be used to integrate open source LLMs to implement scalable and efficient RAG pipelines. He shows how any kind of data including graph, semi-structured, structured, and unstructured data from a variety of sources and types can be processed, queried, and used to feed large language models for smart, contextually aware answers. Look for his example utilizing Cortex AI, LLAMA, Apache NiFi, Apache Iceberg, Snowflake, open source tools, libraries, and Notebooks. Tim will integrate NiFi, Snowflake and Neo4j Graph Data Science.

Speaker

Timothy Spann

Senior Solutions Engineer, Snowflake

Tim Spann is a senior solutions engineer in financial services, working with Snowflake, Cortex AI, Apache NiFi, Apache Iceberg, Python, Apache Polaris, Streamlit, Cloud Data, Vectors, Data, Generative AI, ML, Hugging Face, Apache Kafka, Apache Flink, Pytorch, big data, IoT, machine learning, and deep learning. Tim has more than a decade of experience with IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a principal developer advocate at Zilliz/Milvus, principal developer advocate at Cloudera, developer advocate at StreamNative, principal field engineer at Cloudera, senior solutions architect at AirisData, and a senior field engineer at Pivotal. Tim blogs for DZone, where he is the Big Data Zone leader and runs a popular meetup in Princeton on big data, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds bachelor's and master's degrees in computer science. https://medium.com/@tspann https://www.youtube.com/@FLaNK-Stack https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html