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Azure Databricks

Azure Databricks

Fast, easy, and collaborative Apache Spark–based analytics service

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14-day trial—includes free Databricks Units

Announcement

Azure Databricks – VNet injection, DevOps Version Control and Delta availability

Overview

Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.

Set up your Spark environment in minutes and autoscale quickly and easily. Data scientists, data engineers, and business analysts can collaborate on shared projects in an interactive workspace. Apply your existing skills with support for Python, Scala, R, and SQL, as well as deep learning frameworks and libraries like TensorFlow, Pytorch, and Scikit-learn. Native integration with Azure Active Directory (Azure AD) and other Azure services enables you to build your modern data warehouse and machine learning and real-time analytics solutions.

Why Azure Databricks?

Productive

Launch your new Apache Spark environment in minutes. Seamlessly integrate with other Azure services in an interactive workspace.

Scalable

Globally scale your analytics and machine learning projects. Reduce cost and complexity with a managed platform that autoscales up and down.

Trusted

Help protect your data and business with Azure AD integration, role-based controls, and enterprise-grade SLAs.

Flexible

Build machine learning and AI solutions with your choice of language and deep learning frameworks.

What comes with Azure Databricks?

Optimized Apache Spark environment

Spin up clusters and build quickly in a managed Apache Spark environment. Clusters are set up, configured, and fine-tuned to ensure high reliability and performance.

Autoscale and autoterminate

Reduce resources and costs associated with scaling clusters manually by autoscaling up and down with your needs. Autoterminate your inactive clusters to save resources.

Collaborative workspace

An interactive workspace enables data engineers, data scientists, and business users to collaborate and comment on shared projects as a team.

Optimized for deep learning

Easily build, train, and deploy AI models at scale using GPU-enabled clusters. Use runtime for machine learning that comes preinstalled and preconfigured with deep learning frameworks and libraries such as TensorFlow, Keras, and XGBoost.

Integration with Azure services

Integrate effortlessly with a wide variety of data stores and services such as Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Storage, Azure Event Hubs, and Azure Data Factory. Enable single sign-on with Azure AD to unlock role-based controls.

Support for multiple languages and libraries

Azure Databricks supports languages like Python, Scala, R, and SQL so you can use your existing skills to start building. Target any amount of data or any project size using a comprehensive set of analytics technologies including SQL, Streaming, MLlib, and GraphX.

Analytics and Machine Learning with Azure Databricks

Step 1 of 6

Launch workspace

Navigate to Azure Databricks in the Azure portal. Then log in using single sign-on with Azure AD.

Step 2 of 6

Spin up clusters

Create a new cluster, configure it as you like, and spin it up with one click. The autoscaling feature makes scaling clusters fast and easy. It also helps reduce resources and costs associated with manual scaling.

Step 3 of 6

Collaborate with notebooks

Create custom permission settings for data engineers, data scientists, and business users so each contributor can collaborate live and comment on shared projects based on individual access level.

Step 4 of 6

Explore data

Notebooks support most data languages like SQL, Python, Scala, and R. Data engineers and data scientists can easily mount storage and use the findings to build machine learning models. Business users can see data in easy-to-read live data displays.

Step 5 of 6

Build data science models

Build, train, and deploy AI models at scale using the language of your choice.

Step 6 of 6

Schedule jobs

Run notebooks as jobs in just a few minutes. Choose from existing streaming or machine learning libraries. Schedule jobs in advance to run automatically, and monitor their performance.

What can you do with Azure Databricks

Modern data warehouse

Easily bring together all your data at any scale, and get insights through analytical dashboards, operational reports, and advanced analytics for all your users with a modern data warehouse.

Advanced analytics on big data

Transform your data into actionable insights using best-in-class machine learning tools. This architecture allows you to combine any data at any scale, and to build and deploy custom machine learning models.

Real-time analytics

Get insights from streaming data with ease. Capture data continuously from any streaming source, or logs from website clickstreams, and process it in near-real time.