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Data Intelligence Platform in Azure Databricks is revolutionizing the Data and AI landscape. This fully managed service, which is built on Lakehouse architecture supported by Delta Lake, and is integrated with Microsoft Azure cloud capabilities, streamlines data, analytics, and AI initiatives by removing infrastructure concerns. The close partnership between Databricks and Microsoft enhances this integration, enabling users to focus on their data and AI goals and makes Azure the optimal public cloud for Databricks.
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Data Intelligence Platform in Azure Databricks is revolutionizing the Data and AI landscape. This fully managed service, which is built on Lakehouse architecture supported by Delta Lake, and is integrated with Microsoft Azure cloud capabilities, streamlines data, analytics, and AI initiatives by removing infrastructure concerns. Databricks was recently named a Leader in the 2024 Forrester Wave for Data Lakehouses, earning the highest scores in both strategy and current offerings, and excelling in areas like GenAI/LLM, integration, and security. The close partnership between Databricks and Microsoft enhances this integration, enabling users to focus on their data and AI goals and makes Azure the optimal public cloud for Databricks.
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The platform’s Data Intelligence Engine, DatabricksIQ, is powered by advanced generative AI models to autonomously optimize performance and infrastructure based on the unique characteristics of your data and workloads. Supporting both structured and unstructured data in the Delta Lake format, Azure Databricks combines the best elements of data lakes and data warehouses into a unified system for data storage, processing, security, and governance, facilitating efficient management of data and AI assets at scale.
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Enhanced Data Governance with Unity Catalog in Azure Databricks
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Data and AI governance serves as the intricate yet pivotal foundation for data and AI democratization. Azure Databricks offers a unified solution for data and AI governance with Unity Catalog, natively built into the platform. Unity Catalog uniquely manages data and data assets (such as models) and provides coherent governance across all workloads from analytics to ETL to model serving. It provides centralized access control, auditing, lineage, and AI-powered data documentation and discovery across Azure Databricks workspaces. Leveraging Delta Uniform, Unity Catalog can also provide compatibility for any data format (including Hudi or Iceberg), with a single copy of structured and unstructured data, and federate existing data stores without having to copy data.
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DatabricksIQ works with Unity Catalog in Azure Databricks to develop semantic intelligence about your data. Tables and columns are automatically documented to ensure all data is properly understood. Intelligent search capabilities then assist all users in discovering the tables, notebooks, models, and dashboards most relevant to what they need and have access rights to use.
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DatabricksIQ works with Unity Catalog to enable AI-powered optimization, monitoring, and observability. Unity Catalog in Azure Databricks also ensures data integrity and consistency across workspaces, facilitating collaboration and regulatory compliance. Administrators can set fine-grained access policies, track data provenance in real-time, and manage a comprehensive inventory of data and AI assets like AI models, features, and notebooks. Additionally, Unity Catalog facilitates automated monitoring, error diagnosis, data quality maintenance, and proactive alerts for issues like personally identifiable information (PII) breaches and model drift. Built-in system tables for billing, auditing, and compute provide 360° observability into operations.
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Finally, Unity Catalog in Azure Databricks makes it easy to collaborate among data teams with native support for Delta Sharing, an open source standard for securely sharing files, tables, AI models, notebooks, and dashboards across clouds, regions and data platforms.
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Advanced Data Warehousing with Azure Databricks SQL
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Building on these foundational capabilities, Azure Databricks SQL (DBSQL) provides intelligent data warehousing capabilities and integrates seamlessly with Power BI in Microsoft Fabric, enabling users to perform complex analytics and derive insights from their data. DB SQL supports SQL-based querying, allowing users to interact with data using familiar language constructs. The integration with Power BI is facilitated through a native Databricks connector, which supports secure and efficient data delivery directly from the Lakehouse. Additionally, DBSQL provides advanced features such as support for streaming tables, materialized views, window functions, user-defined functions, and AI Functions, empowering data analysts and data scientists to tackle sophisticated analytical tasks simply.
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DBSQL is powered by DatabricksIQ. Predictive capabilities help ensure optimal query price/performance. Data analyst and developer productivity is also enhanced through text-to-SQL assistance to author code, remediate errors, and explain documentation.
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Zero-management computation at scale with Serverless
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Azure Databricks is one click away in the Azure Portal, and warehousing, ETL, or machine learning can be leveraged while letting Azure handle all of the machine provisioning and orchestration in the new Serverless capabilities. This leverages AI to prewarm capacity, autoscaling to your needs and charging you when your code runs.
Beyond data management and analysis, Mosaic AI within Azure Databricks addresses the growing demand for both Generative AI and traditional AI use cases, tightly connected to all of your enterprise data. Mosaic AI is an end-to-end solution for building, deploying, and monitoring AI - from predictive modeling to the latest GenAI and large language models (LLMs) on top of Unity Catalog, but it is challenging to operationalize LLM applications in IT environment. As a core component of Azure Databricks, Mosaic AI LLMOps enables organizations to securely and cost-effectively integrate their enterprise data into the AI and GenAI lifecycle. Mosaic AI Retrieval Augmented Generation (RAG) platform enables organization to easily use their enterprise data to augment and fine-tune LLMs like Azure OpenAI, DBRX, or Meta Llama 3. Users can also build their own custom LLMs from scratch with their own data, reducing LLM hallucination risk, and powering it with a semantic understanding of their business without sending data and IP outside their walls. Azure Databricks RAG platform architecture is illustrated in the following diagram.
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Mosaic AI offers this flexibility while maintaining governance, monitoring, and security across the full AI/ML lifecycle from data to models to meet the most stringent compliance requirements. These capabilities collectively allow organizations to deliver production-quality AI applications that are accurate, safe, and well-governed with Azure Databricks.
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In summary, Azure Databricks is infused with AI, making it the simplest, most unified way to bring intelligence to all your data and AI needs. Azure Databricks as Data Intelligence Platform, offers a comprehensive solution for organizations seeking to harness the power of their data -. With robust governance, advanced data warehousing capabilities, and transformative MLOps, LLMOps, generative AI features, and deep seamless integration with Azure services and workloads, Azure Databricks empowers data-driven decision-making and innovation at scale.
Data Intelligence Platform in Azure Databricks is revolutionizing the Data and AI landscape. This fully managed service, which is built on Lakehouse architecture supported by Delta Lake, and is integrated with Microsoft Azure cloud capabilities, streamlines data, analytics, and AI initiatives by removing infrastructure concerns. Databricks was recently named a Leader in the 2024 Forrester Wave for Data Lakehouses, earning the highest scores in both strategy and current offerings, and excelling in areas like GenAI/LLM, integration, and security. The close partnership between Databricks and Microsoft enhances this integration, enabling users to focus on their data and AI goals and makes Azure the optimal public cloud for Databricks.
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The platform’s Data Intelligence Engine, DatabricksIQ, is powered by advanced generative AI models to autonomously optimize performance and infrastructure based on the unique characteristics of your data and workloads. Supporting both structured and unstructured data in the Delta Lake format, Azure Databricks combines the best elements of data lakes and data warehouses into a unified system for data storage, processing, security, and governance, facilitating efficient management of data and AI assets at scale.
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Enhanced Data Governance with Unity Catalog in Azure Databricks
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Data and AI governance serves as the intricate yet pivotal foundation for data and AI democratization. Azure Databricks offers a unified solution for data and AI governance with Unity Catalog, natively built into the platform. Unity Catalog uniquely manages data and data assets (such as models) and provides coherent governance across all workloads from analytics to ETL to model serving. It provides centralized access control, auditing, lineage, and AI-powered data documentation and discovery across Azure Databricks workspaces. Leveraging Delta Uniform, Unity Catalog can also provide compatibility for any data format (including Hudi or Iceberg), with a single copy of structured and unstructured data, and federate existing data stores without having to copy data.
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DatabricksIQ works with Unity Catalog in Azure Databricks to develop semantic intelligence about your data. Tables and columns are automatically documented to ensure all data is properly understood. Intelligent search capabilities then assist all users in discovering the tables, notebooks, models, and dashboards most relevant to what they need and have access rights to use.
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DatabricksIQ works with Unity Catalog to enable AI-powered optimization, monitoring, and observability. Unity Catalog in Azure Databricks also ensures data integrity and consistency across workspaces, facilitating collaboration and regulatory compliance. Administrators can set fine-grained access policies, track data provenance in real-time, and manage a comprehensive inventory of data and AI assets like AI models, features, and notebooks. Additionally, Unity Catalog facilitates automated monitoring, error diagnosis, data quality maintenance, and proactive alerts for issues like personally identifiable information (PII) breaches and model drift. Built-in system tables for billing, auditing, and compute provide 360° observability into operations.
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Finally, Unity Catalog in Azure Databricks makes it easy to collaborate among data teams with native support for Delta Sharing, an open source standard for securely sharing files, tables, AI models, notebooks, and dashboards across clouds, regions and data platforms.
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Advanced Data Warehousing with Azure Databricks SQL
\n
Building on these foundational capabilities, Azure Databricks SQL (DBSQL) provides intelligent data warehousing capabilities and integrates seamlessly with Power BI in Microsoft Fabric, enabling users to perform complex analytics and derive insights from their data. DB SQL supports SQL-based querying, allowing users to interact with data using familiar language constructs. The integration with Power BI is facilitated through a native Databricks connector, which supports secure and efficient data delivery directly from the Lakehouse. Additionally, DBSQL provides advanced features such as support for streaming tables, materialized views, window functions, user-defined functions, and AI Functions, empowering data analysts and data scientists to tackle sophisticated analytical tasks simply.
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DBSQL is powered by DatabricksIQ. Predictive capabilities help ensure optimal query price/performance. Data analyst and developer productivity is also enhanced through text-to-SQL assistance to author code, remediate errors, and explain documentation.
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Zero-management computation at scale with Serverless
\n
Azure Databricks is one click away in the Azure Portal, and warehousing, ETL, or machine learning can be leveraged while letting Azure handle all of the machine provisioning and orchestration in the new Serverless capabilities. This leverages AI to prewarm capacity, autoscaling to your needs and charging you when your code runs.
Beyond data management and analysis, Mosaic AI within Azure Databricks addresses the growing demand for both Generative AI and traditional AI use cases, tightly connected to all of your enterprise data. Mosaic AI is an end-to-end solution for building, deploying, and monitoring AI - from predictive modeling to the latest GenAI and large language models (LLMs) on top of Unity Catalog, but it is challenging to operationalize LLM applications in IT environment. As a core component of Azure Databricks, Mosaic AI LLMOps enables organizations to securely and cost-effectively integrate their enterprise data into the AI and GenAI lifecycle. Mosaic AI Retrieval Augmented Generation (RAG) platform enables organization to easily use their enterprise data to augment and fine-tune LLMs like Azure OpenAI, DBRX, or Meta Llama 3. Users can also build their own custom LLMs from scratch with their own data, reducing LLM hallucination risk, and powering it with a semantic understanding of their business without sending data and IP outside their walls. Azure Databricks RAG platform architecture is illustrated in the following diagram.
\n
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Mosaic AI offers this flexibility while maintaining governance, monitoring, and security across the full AI/ML lifecycle from data to models to meet the most stringent compliance requirements. These capabilities collectively allow organizations to deliver production-quality AI applications that are accurate, safe, and well-governed with Azure Databricks.
\n
\n
In summary, Azure Databricks is infused with AI, making it the simplest, most unified way to bring intelligence to all your data and AI needs. Azure Databricks as Data Intelligence Platform, offers a comprehensive solution for organizations seeking to harness the power of their data -. With robust governance, advanced data warehousing capabilities, and transformative MLOps, LLMOps, generative AI features, and deep seamless integration with Azure services and workloads, Azure Databricks empowers data-driven decision-making and innovation at scale.
Data Intelligence Platform in Azure Databricks is revolutionizing the Data and AI landscape. This fully managed service, which is built on Lakehouse architecture supported by Delta Lake, and is integrated with Microsoft Azure cloud capabilities, streamlines data, analytics, and AI initiatives by removing infrastructure concerns. The close partnership between Databricks and Microsoft enhances this integration, enabling users to focus on their data and AI goals and makes Azure the optimal public cloud for Databricks.
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