
Discover effective strategies for unit testing streaming jobs, addressing challenges like long-running processes and third-party dependencies to improve data quality and code reliability.

Explore Databricks' foundational models like DBRX, their capabilities, and applications. Learn to leverage these models for enhanced data analytics and machine learning projects across industries.

Explore ultra low-latency data processing advancements, new stateful processing capabilities, and the future of streaming pipelines. Learn how to deliver real-time data for top AI use cases across industries.

Riot Games leverages data observability to ensure high-quality data for millions of gamers. Learn how they built a robust Databricks Lakehouse architecture and used Monte Carlo to scale data reliability efficiently.

Discover Atlassian's innovative data lakehouse redesign, exploring account structures, workbench environments, Unity Catalog integration, and declarative approaches for enhanced data management and ML governance.

Discover how Diageo leveraged Databricks' Unity Catalog to centralize data, implement a lakehouse architecture, and unlock new opportunities in their data roadmap, including simplified hub-and-spoke model implementation.

Discover Graphite: a unified app for querying content lifecycle data, offering real-time insights into revenue streams using Databricks technologies and natural language querying for transformative data interaction.

Simplify workloads with serverless compute on Databricks: eliminate cluster setups, enhance start times, optimize resources, and improve reliability while maximizing cost-efficiency and performance.

Learn strategies for migrating from Snowflake to Databricks, including methodology, technical approaches, automation tools, and best practices. Gain insights from real-world case studies on data, ELT pipeline, and warehouse migration.

Explore Databricks' journey in building a Metric Store, solving data inconsistencies, and unlocking advanced analytics capabilities for unified, forecasted, and explainable metrics across the organization.

Explore CDC's enhanced big data processing for public health visualizations, optimizing respiratory illness monitoring through efficient data management and accelerated insight delivery.

Explore GPU hardware's role in generative AI, AMD's advancements, and Databricks' solutions for scalable model training, deployment, and governance while ensuring data privacy and cost-effectiveness.

Discover how to scale MLOps for high-frequency retraining of 50k models weekly using Databricks, MLflow, and Pandas UDFs. Learn best practices for experiment tracking, code consistency, and handling data volatility at scale.

Explore Mosaic AI's tools for streamlining GenAI application development, deployment, and management. Learn best practices for efficient AI project creation on a secure Data Intelligence platform.

Explore innovative data architecture solutions combining Medallion and Data Mesh patterns to enhance productivity, democratize data access, and ensure scalable, efficient data management in large organizations.

Discover how a financial company implemented RAG to enhance customer service, exploring architecture, data pipelines, innovations, and optimization strategies for transforming operations with Generative AI.

Explore Mosaic AI for efficient GenAI app development on Databricks. Learn design, maintenance, and integration techniques through practical demonstrations to streamline your AI projects.

Explore the design of an AI copilot for data transformation, focusing on unique challenges and solutions to enhance productivity. Includes demos and insights on LLM applications in programming.

Accelerate digital transformation with unified data and AI governance using Unity Catalog. Learn how to manage platform objects, remove barriers, and achieve AI ambitions at enterprise scale.

Learn to create production-ready, high-quality data products using Databricks. Explore lifecycle requirements, challenges, and best practices to establish a trustworthy foundation for AI and data-driven initiatives.

Explore Databricks' Lakehouse Observability approach, integrating tools for monitoring and optimizing data and AI workflows to support scalable, data-driven applications.