Groß angelegte Datenverarbeitung für Batch- und Streaming-Workloads.
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Vereinfachung und Beschleunigung von Data Science bei großen Datensätzen.
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Standardisierung des ML-Lebenszyklus vom Experiment bis zur Produktion.
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See how you can easily query your data lake using SQL and Delta Lake on Azure. We’ll show how Delta Lake enables you to run SQL queries without moving or copying your data. We will also explain some of the added benefits that Azure Databricks provides when working with Delta Lake.
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Deploy auto-scaling compute clusters with highly-optimized Spark that perform up to 50x faster.
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Azure Databricks is trusted by thousands of customers who run millions of server hours each day across more than 30 Azure regions.
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Start with a single click in the Azure Portal, natively integrate with Azure security and data services, and boost productivity by up to 25% with collaborative data engineering and data science.
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Databricks, Microsoft and our partners are excited to host these events dedicated to Azure Databricks. Please join us at an event near you to learn more about the fastest-growing Data + AI service on Azure! The agenda and format will vary, please see the specific event page for details.
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Single Sign-On with Azure Active Directory is the best way to sign in to Azure Databricks. Azure Databricks also supports automated user provisioning with Azure AD to create new users, give them the proper level of access, and remove users to deprovision access.
The Azure Databricks native connector to ADLS supports multiple methods of access to your data lake. Simplify data access security by using the same Azure AD identity that you use to log into Azure Databricks with Azure Active Directory Credential Passthrough. Your data access is controlled via the ADLS roles and Access Control Lists you have already set up.
Seamlessly run Azure Databricks jobs using Azure Data Factory and leverage 90+ built-in data source connectors to ingest all of your data sources into a single data lake. ADF provides built-in workflow control, data transformation, pipeline scheduling, data integration, and many more capabilities to help you create reliable data pipelines.
Azure Databricks integrates with Microsoft Azure Machine Learning (AML) via MLflow to centrally track ML experiments and deploy models to Azure containers for on-demand inferencing. Azure Databricks can also use AML’s automated machine learning capabilities through the AML SDK.
Azure Databricks integrates with Azure Synapse to bring analytics, business intelligence (BI), and data science together in Microsoft’s Modern Data Warehouse solution architecture. The high-performance connector between Azure Databricks and Azure Synapse enables fast data transfer between the services, including support for streaming data.
Azure Databricks connects with Azure DevOps to help enable Continuous Integration and Continuous Deployment (CI/CD). Configure Azure DevOps as your Git provider and take advantage of the integrated version control features.
The default deployment of Azure Databricks is a fully managed service on Azure that includes a virtual network (VNet). Azure Databricks also supports deployment in your own virtual network (sometimes called VNet injection) that enables full control of network security rules.
Get insights from live streaming data by connecting Azure Event Hubs to Azure Databricks, then process messages as they arrive. With Event Hubs and Azure Databricks, stream millions of events per second from any IoT device, or logs from website clickstreams, and process it in near-real time.
Manage your secrets such as keys and passwords with integration to Azure Key Vault. By default, all Azure Databricks notebooks and results are encrypted at rest with a different encryption key. If you want to own and manage the key used for encrypting your notebooks and results yourself, you can bring your own key (BYOK).
Process all of your data in real time to provide the most relevant product and service recommendations.
Modernize your technology stack to improve experience for patients and physicians with the fastest DNASeq pipeline at scale.
Leverage complete historical data together with real-time data streams to quickly identify anomalous and suspicious financial transactions.
Azure Databricks für Data Engineering
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Modernize with On-premises Hadoop to Azure Databricks Migration
How Starbucks Forecasts Demand at Scale with Facebook Prophet and Azure Databricks
Using SQL to Query Your Data Lake with Delta Lake
From Data to AI with Microsoft Azure Databricks
Deep Learning at Scale with PyTorch, Azure Databricks, and Azure Machine Learning