This video demonstrates how to use an open source pre-trained instruction-following LLM (Large Language Model) to build a ChatBot-like web application. The responses of the LLM are enhanced by giving it context from an internal knowledge base. This context is retrieved by using an open source Vector Database to do semantic search.

Cloudera Machine Learning offers a comprehensive solution for the full machine learning lifecycle, from finding and exploring data to hosting custom ML web apps. With nearly 700 enterprise customers using ML in production, it provides a trusted and efficient way to deploy complex models and support a diverse range of AI use cases.

This demo shows how easy it is to get started with the Cloudera Data Warehouse. We’ll cover data ingestion, data security, running queries using our SQL editor, and optimizations for improving query performance using a simple business use case. Learn more at cloudera.com/demos

Cloudera Data Warehouse is a comprehensive data analytics and management solution that offers security and governance policies, automations, and high-speed SQL engines for analyzing data easily, self-service, and quickly. Its open data lakehouse architecture eliminates data silos, making all data accessible without moving it, and due to integration with Apache Iceberg, supports both structured and unstructured, real-time, and batch data.

In this demo, see how platform administrators and data engineers can use Cloudera Data Engineering as an all-inclusive toolset to streamline ETL processes across enterprise analytics teams.

Cloudera Data Engineering is a cloud-native service that provides an all-inclusive toolset for orchestrating and automating complex data pipelines, with built-in visual monitoring. It is fully integrated with the Cloudera Data Platform and enables data to be used by any data engineering team enabling analytics or ML across the business-delivering curated, quality datasets securely and transparently across all use cases.

Cloudera Stream Processing lets developers and analysts build real-time data products using industry-standard SQL. In this demo, you will see SQL Stream Builder quickly transform Kafka topics into tables to be queried and SQL queries transformed into continuous Flink jobs.

Cloudera Data in Motion is designed to enable businesses to respond to critical events in real-time and streamline their data capture, processing, and distribution, while maintaining security and governance. It offers an open architecture for maximum flexibility and control over resources, addressing data in motion challenges.

In this product demo, we cover key sections of Cloudera DataFlow for the Public Cloud, including its dashboard; ReadyFlow Gallery; and DataFlow Functions that can run NiFi flows in AWS, Azure, or Google Cloud Platform serverless compute environments.

In the age of connected everything, insurers face new challenges and opportunities as they strive to deliver personalized insurance coverage while minimizing costs and preventing fraud. With the Cloudera Data Platform, insurers can unlock the power of real-time data and analytics to make insurance more precise, more personalized, and more profitable. By building a 360-view of each customer, streamlining claims and services, and unlocking usage-based insurance with IoT sensor data, insurers can manage risks and create opportunities to transform for today and stay ahead tomorrow.