Andreessen Horowitz
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With Databricks, lineage, quality, control and data privacy are maintained across the entire AI workflow, powering a complete set of tools to deliver any AI use case. Create, tune and deploy your own generative AI models
Databricks is a unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale. The Databricks Data Intelligence Platform integrates with cloud storage and security in your cloud account, and manages and deploys cloud infrastructure on your behalf.
Explore Databricks resources for data and AI, including training, certification, events, and community support to enhance your skills.
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Discover why businesses are turning to Databricks to accelerate innovation. Try Databricks’ Full Platform Trial free for 14 days!
Manage model lifecycle. MLflow experiment tracking. AI and Machine Learning on Databricks, an integrated environment to simplify and standardize ML, DL, LLM, and AI development. Tutorials and user guides for common tasks and scenarios.
Databricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers solving problems in analytics and AI. The Databricks Data Intelligence Platform enables data teams to collaborate on data stored in the lakehouse.
Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.
Azure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI and other Azure services to store all your data on a simple, open lakehouse and unify all your analytics and AI workloads.
Databricks, Inc. is a global data, analytics and artificial intelligence company founded by the original creators of Apache Spark. [3] The company provides a cloud-based platform to help enterprises build, scale, and govern data and AI, including generative AI and other machine learning models. [4]
