Analytics projects need more than just data—they need a strong business case. Iris breaks down how to balance costs and benefits, structure your approach, and track the business impact from start to finish.
After this year’s Current 2024 conference, the future of Kafka seems to be in flux. Yingjun explores how AI and evolving data streaming technologies influence Kafka’s role in the real-time analytics world.
Learn how to build a robust RAG system with Postgres. Eric walks through every step—setting up data pipelines to optimizing retrieval for high-performance AI-driven responses.
AI agents are getting more powerful, but how do you choose the proper framework? Aparna compares new frameworks like LangGraph and LlamaIndex Workflows, giving practical insights on building agents from scratch versus leveraging existing tools.
Want to automate syncing your dbt models with Looker? Silja shows how her team replaced manual LookML writing with an automated process, ensuring the latest models and metrics are always at hand for Looker users.
This paper introduces FRAMES, a dataset designed to assess the performance of LLMs in retrieval-augmented systems. The team evaluates factual accuracy, retrieval efficiency, and reasoning abilities, making it a must-read for those building cutting-edge RAG solutions.
Langfun makes working with language models feel like a breeze. Powered by PyGlove, it treats language as functions and allows object-oriented prompting—offering more control over how you interact with LLMs. Worth checking out for those working on LLM-powered applications!
Curious about GraphRAG and its practical use cases? Prashanth Rao joins the show to break down GraphRAG and what it means for the future of graph data. If you’re hearing a lot of buzz around this topic, this episode is a great place to cut through the hype.
How they managed to store over 500TB of audit data, with a cost under 500/mo and a fast response time, no matter how big the query time range is.
This is the unique journey of locating, classifying, and effectively storing 0.5PB of customer data. A distinctive setup leveraging Google BigQuery technology enabled the support & compliance team to execute complex queries against the entire dataset with a remarkable response time of 11s.
BTW as a community partner, we have a discount for Infoshare DEV; there will be more presentations like this. Buy discounted tickets here.
Databricks + VS Code = a dream for many data engineers. This video covers setting it up and leveraging the new features in the latest Databricks extension. From deploying code to avoiding common pitfalls—this demo has it all.
Whether you're in Gdynia or tuning in online, this AWS User Group event will not be noticed! Connect with professionals, sharpen your skills, and learn about the latest GenAI developments. Save the date!