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Microsoft Azure Databricks

Azure Databricks is an analytics platform optimized for the Microsoft Azure cloud service platform. Azure Databricks offers three environments for developing data-intensive applications: Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning.

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What Is Azure Databricks?

With Azure Databricks, companies gain new insights and can build analytics solutions for artificial intelligence (AI). Users set up their Apache Spark™ environment in minutes, automatically scale it, and collaborate on collaborative projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries such as TensorFlow, PyTorch, and Scikit-Learn.

Azure Databricks offers three environments for developing data-intensive applications: Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning.

Azure Databricks SQL

Databricks SQL provides an easy-to-use platform for analysts who want to create SQL queries against their data lake, create multiple visualization types to explore query results from different perspectives, and create and share dashboards.

Azure Databricks data science & engineering

Databrick’s Data Science & Engineering provides an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning engineers. For a big data pipeline, raw or structured data is collected in batches through Azure Data Factory in Azure or streamed in near real time using Apache Kafka, Event Hub, or IoT Hub. This data is stored in a data lake (Azure Blob Storage or Azure Data Lake Storage) for the long term.

Azure Databricks machine learning

Databrick’s Machine Learning is an integrated, end-to-end machine learning environment with managed services for experiment tracking, model training, feature development and management, and feature and model deployment.

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The Benefits of Azure Databricks

Reliable data technology

Extensive data processing for batch and streaming workloads

Analysis for all data

Complete and up-to-date data through analysis

Collaborative Data Science

Simpler and faster data science for large datasets

Open source based

Fast, optimized Apache Spark environment

Get Started With Azure Databricks

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Get started quickly with an optimized Apache Spark environment

Azure Databricks includes the latest version of Apache Spark, allowing users to seamlessly integrate with open source libraries. Spinup clusters in a fully managed Apache Spark environment with the worldwide availability of Microsoft Azure. Azure Databricks sets up, configures, and then optimizes clusters to ensure superior reliability and performance without the need for monitoring. Azure Databricks provides auto-scaling and auto-stop to reduce overall costs.

Azure Databricks - Work Together

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Azure Databricks: Increase productivity with a shared workspace and many languages 

With Azure Databricks, users work together effectively on an open, unified platform.  They can run any analytics workload, whether they are data scientists, data technical professionals, or  business analysts. Azure Databricks offers the possibility to work in the user’s preferred language – whether  Python, Scala, R or SQL. Easily control notebook version control with GitHub and Azure DevOps. 

Machine Learning with Azure Databricks

Azure Databricks: Powerful machine learning capabilities for big data

With Azure Databricks, users can leverage complex automated machine learning capabilities thanks to the built-in Azure Machine Learning service to quickly determine appropriate algorithms and hyperparameters.  This makes it easier for organizations to manage, monitor, and update machine learning models deployed from the cloud to the edge. Azure Machine Learning also provides a central registry for experiments, machine learning pipelines, and models.

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Azure Databricks - Data Warehousing Support

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Azure Databricks supports powerful, modern data warehousing

Azure Databricks supports the optimal analytics workflows for businesses, from combining all relevant data to gaining insights using analytics dashboards and reporting. The starting point is to automate data integration with Azure Data Factory, then load the data into Azure Data Lake Storage, transform and manage with Azure Databricks, and deploy it for analysis with Azure Synapse Analytics. This is how organizations modernize their data warehouse in the cloud for unmatched performance and scalability.

Key Service Features of Azure Databricks

Optimized Spark engine

Azure Databricks provides easy data processing in an auto-scaling infrastructure, and enterprises benefit from up to a 50x performance boost thanks to the highly optimized Apache Spark™ engine.

MLflow

With Azure Databricks, data scientists monitor experiments, share them, reproduce the test runs, and manage models together in a central repository.

Collaborative Notebooks

With Azure Databricks, users can quickly access and analyze data to gather information and make better decisions. In addition, data scientists can develop models together with the tools and languages of their choice.

Selection of languages

Azure Databricks allows users to use their preferred language, including Python, Scala, R, Spark SQL, and .NET, for serverless or provisioned compute resources as they type.

Delta Lake

With Azure Databricks, organizations make existing data lakes more reliable and scalable by leveraging an open-source storage layer for transactions designed for the entire data lifecycle.

Native integration with Azure-Diensten

Complement your analytics and machine learning solution by working closely with Azure services such as Azure Data Factory, Azure Data Lake Storage, Azure Machine Learning and Power BI.

Enterprise-grade security

Azure Databricks' easy-to-use, native security features protect the data in the location so that analytics workspaces are always compliant, private, and isolated for thousands of users and datasets.

Ready for production

With Azure Databricks, users run mission-critical data workloads at scale on a trusted data platform that provides integrations for CI/CD and monitoring solutions.

Machine Learning Runtime

Azure Databricks provides one-click access to preconfigured machine learning environments to extend machine learning processes with modern and popular frameworks such as PyTorch, TensorFlow, and scikit-learn.

Interaktive workspaces

With Azure Databricks, organizations enable seamless collaboration between data scientists, data engineers, and business analysts.

areto’s Microsoft Azure Reference Architecture

Areto’s developed Microsoft Azure reference architecture offers many advantages.

The use of areto’s Microsoft Azure reference architecture provides customers with best practices for developing and operating reliable, secure, efficient and cost-effective systems in the cloud. Areto’s Microsoft Azure architecture solutions are consistently measured against Microsoft best practices in order to deliver the highest benefit to customers.

The areto Microsoft Azure reference architecture is based on five pillars: operational excellence, security, reliability, performance efficiency, cost optimization.

Operational excellence
optimal design of operation and monitoring of the systems as well as continuous improvement of supporting processes and procedures

Security
protection of information, systems, assets, risk assessments and risk mitigation strategies

Cost optimization
maximizing ROI through the continuous process of improving the system throughout its lifecycle. .

Reliability
ensure security, disaster recovery, business continuity as data is mirrored in multiple redundant locations.

Performance efficiency
efficient use of computer resources, scalability to meet short-term requirement peaks, sustainability

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Free consulting & demo appointments

Do you already have a strategy for your future Micrsoft Data Analytics solution? Are you already taking advantage of modern cloud platforms and automation? We would be happy to show you examples of how our customers are already using areto’s agile and scalable Microsoft solutions.

Workshops / Coachings

In our Microsoft workshops and coaching sessions, you will gain the necessary know-how, e.g. for setting up a modern cloud strategy or IBCS-compliant reporting with Power BI . The areto Microsoft TrainingCenter offers a wide range of learning content

Proof of Concepts

Is Azure the right fit for us? Are the framework conditions suitable for it? What prerequisites need to be created? Proof of concepts (POCs) answer these and other questions. This way, you start your project well prepared. 

Why Microsoft ?

2021 CIPS MQ 2

Gartner, Magic Quadrant for Cloud Infrastructure & Platform Services, Raj Bala, Bob Gill, Dennis Smith, Kevin Ji, David Wright, 27 July 2021. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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Florian Grell
Teamlead Microsoft
Phone: +49 221 66 95 75-0
E-mail: Florian.Grell@areto.de

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