Azure Databricks combines the power of Apache Spark with Delta Lake and custom tools to provide an unrivaled ETL (extract, transform, load) experience. Whether you’re generating dashboards or powering artificial intelligence applications, data engineering provides the backbone for data-centric companies by making sure data is available, clean, and stored in data models that allow for efficient discovery and use. Data engineers, data scientists, analysts, and production systems can all use the data lakehouse as their single source of truth, allowing timely access to consistent data and reducing the complexities of building, maintaining, and syncing many distributed data systems. The data lakehouse combines the strengths of enterprise data warehouses and data lakes to accelerate, simplify, and unify enterprise data solutions. The following use cases highlight how users throughout your organization can leverage Azure Databricks to accomplish tasks essential to processing, storing, and analyzing the data that drives critical business functions and decisions. Use cases on Azure Databricks are as varied as the data processed on the platform and the many personas of employees that work with data as a core part of their job. What are common use cases for Azure Databricks? It removes many of the burdens and concerns of working with cloud infrastructure, without limiting the customizations and control experienced data, operations, and security teams require. Azure Databricks makes it easy for new users to get started on the platform. Unity Catalog further extends this relationship, allowing you to manage permissions for accessing data using familiar SQL syntax from within Azure Databricks.Īzure Databricks workspaces meet the security and networking requirements of some of the world’s largest and most security-minded companies. Instead, you configure an Azure Databricks workspace by configuring secure integrations between the Azure Databricks platform and your cloud account, and then Azure Databricks deploys compute clusters using cloud resources in your account to process and store data in object storage and other integrated services you control. Unlike many enterprise data companies, Azure Databricks does not force you to migrate your data into proprietary storage systems to use the platform. The customer-owned infrastructure managed in collaboration by Azure Databricks and your company.The infrastructure used by Azure Databricks to deploy, configure, and manage the platform and services.The Azure Databricks platform architecture comprises two primary parts: How does Azure Databricks work with Azure? The following technologies are open source projects founded by Databricks employees:Īzure Databricks maintains a number of proprietary tools that integrate and expand these technologies to add optimized performance and ease of use, such as the following: Databricks manages updates of open source integrations in the Databricks Runtime releases. In addition to the workspace UI, you can interact with Azure Databricks programmatically with the following tools:ĭatabricks has a strong commitment to the open source community. Machine learning (ML) modeling and tracking. Data discovery, annotation, and exploration.Managing security, governance, and HA/DR.Generating dashboards and visualizations.Data processing workflows scheduling and management.The Azure Databricks workspace provides a unified interface and tools for most data tasks, including: Use the Azure Databricks platform to build and deploy data engineering workflows, machine learning models, analytics dashboards, and more. Our customers use Azure Databricks to process, store, clean, share, analyze, model, and monetize their datasets with solutions from BI to machine learning. The Azure Databricks Lakehouse Platform integrates with cloud storage and security in your cloud account, and manages and deploys cloud infrastructure on your behalf. Azure Databricks is a unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale.
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