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Insider look at Databricks' scalable data governance approach using Unity Catalog, covering challenges, solutions, and best practices for enabling secure access to cloud resources and assets.
Proposing a new approach to ML infrastructure: shared, accessible apps and services using PyTorch-like APIs, aiming to overcome fragmentation in enterprise ML and improve scalability.
Explore Atlassian's Data Mesh implementation, multi-regional data lake, and compliance strategies. Learn about logical replication, data contracts, and how the data lake powers various use cases, unlocking team potential.
Explore an insurance company's migration from SAP BW to Databricks, highlighting improved performance, automated ETL, enhanced self-service, and cost reduction. Learn insights and future possibilities.
Explore the symbiosis of data and AI, focusing on high-quality data streams. Learn about AI fundamentals, data's role in model training, and overcoming data management challenges for enhanced decision-making and innovation.
Explore Azure Data Lake Storage's role in scaling analytics and AI, integrating with Azure Databricks for unified data engineering, science, and machine learning on a secure cloud platform.
Centralized data management platform for DOE and NNSA projects, enabling researchers to focus on science while efficiently handling data storage, computation, and curation using Databricks and AI.
Spark-based AutoML framework for scalable time series forecasting of IT infrastructure resources, enabling efficient long-term planning and daily dynamic provisioning.
Unveiling AI trends from 400 senior professionals: Generative AI's rise, ROI challenges, and industry priorities. Gain insights to navigate AI complexities and learn from pioneers executing at scale.
Explore Zalando's journey in adopting Databricks Unity Catalog, overcoming challenges in a large-scale environment with diverse use cases, distributed schemas, and strict regulations to enhance data governance and productivity.
Explore IRC's adoption of data lakehouse architecture using Azure Databricks, enhancing humanitarian efforts through streamlined data processes and improved operational efficiencies.
Discover best practices for monitoring and optimizing Databricks operations using new system tables. Learn to leverage metadata for comprehensive data health management and operational insights.
Practical guide to deploying LLMs in business: evaluation, fine-tuning, data selection, training ecosystems, and workflows for optimal performance and continuous improvement.
Explore WGU's MARVIN platform, addressing MLOps challenges with Databricks. Learn about streamlined workflows, project templates, and strategies for efficient ML model deployment at scale.
Explore advanced BI integrations for Databricks SQL, including seamless connections with Power BI and Tableau, data model syncing, and updates on drivers and connectors.
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