Modern data warehouse

Build the hub for all of your data – structured, unstructured or streaming – to drive transformative solutions like BI and reporting, advanced analytics and real-time analytics. Take advantage of the performance, flexibility and security of fully managed Azure services, such as Azure Synapse Analytics and Azure Databricks, to get started with ease.

Accelerate time to market

Ensure productivity with industry-leading SQL Server and Apache Spark engines, as well as fully managed cloud services that allow you to provision your modern data warehouse in minutes. Accelerate data integration with more than 30 native data connectors from Azure Data Factory and support for leading information management tools from Informatica and Talend. Empower your data scientists, data engineers and business analysts to use the tools and languages of their choice on big data.

Read how Rockwell Automation cut development time by 80 per cent for shorter time to market, reduced costs and improved customer responsiveness.

Choose a solution based on your specific needs

Easily get started with a cloud solution or a hybrid option based on your business requirements. Only Microsoft lets you take consistent advantage of SQL Server performance, familiarity and security in a private cloud or as a managed service in MPP architecture in Azure. Reduce costs and the complexity of managing existing data transformations through the hybrid data integration experience. Finally, enable a consistent user experience with common identity across on-premises services and Azure.

Learn how Carnival Maritime built a hybrid solution that predicts onboard water usage, saving $200000 per ship annually.

Get insights on any data

Take advantage of the flexibility to build and deploy machine learning models on-premises or in the cloud. Use the data science tool of your choice with support for the best of Microsoft and open-source innovation. Easily distribute insights across your organisation through rich integration with Power BI and other leading business intelligence and visualisation tools like Tableau, Qlik, MicroStrategy and Alteryx.

Find out how ASOS delivers 13 million personalised experiences with up to 33 orders per second.

Enjoy peace of mind

Built-in advanced security features include Transparent Data Encryption, audit, threat detection, Azure Active Directory integration and Azure Virtual Network endpoints. Azure services comply with more than 50 industry and geographical certifications, and are globally available across 42 regions to keep your data where your users are. Finally, Microsoft offers financially backed SLAs to ensure peace of mind.

Read why GE Healthcare delivers its core solutions using Azure data services.

Customers doing great things with modern data warehouse

Solution architectures

Entrepôt de données moderneUn entrepôt de données moderne vous permet de regrouper facilement toutes vos données, quelle qu’en soit l’échelle, et d’en extraire des informations pour tous vos utilisateurs grâce à des tableaux de bord analytiques, des rapports opérationnels ou des analyses avancées.12345
  1. Overview
  2. Flow

Modern data warehouse

Overview

A modern data warehouse lets you bring together all your data at any scale easily, and means you can get insights through analytical dashboards, operational reports or advanced analytics for all your users.

Flow

  1. 1 Combine all your structured, unstructured and semi-structured data (logs, files and media) using Azure Data Factory to Azure Blob Storage.
  2. 2 Leverage data in Azure Blob Storage to perform scalable analytics with Azure Databricks and achieve cleansed and transformed data.
  3. 3 Cleansed and transformed data can be moved to Azure Synapse Analytics to combine with existing structured data, creating one hub for all your data. Leverage native connectors between Azure Databricks and Azure Synapse Analytics to access and move data at scale.
  4. 4 Build operational reports and analytical dashboards on top of Azure Data Warehouse to derive insights from the data, and use Azure Analysis Services to serve thousands of end users.
  5. 5 Run ad hoc queries directly on data within Azure Databricks.
Analytique avancée du Big DataConvertissez vos données en informations exploitables à l’aide des meilleurs outils d’apprentissage automatique. Cette architecture vous permet de combiner toutes sortes de données, quelle qu’en soit l’échelle, et de construire et déployer des modèles d’apprentissage automatique à grande échelle.1234567
  1. Overview
  2. Flow

Advanced analytics on big data

Overview

Transform your data into actionable insights using the 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 at scale.

Flow

  1. 1 Bring together all your structured, unstructured and semi-structured data (logs, files and media) using Azure Data Factory to Azure Blob Storage.
  2. 2 Use Azure Databricks to clean and transform the structureless datasets and combine them with structured data from operational databases or data warehouses.
  3. 3 Use scalable machine learning/deep learning techniques to derive deeper insights from this data using Python, R or Scala, with inbuilt notebook experiences in Azure Databricks.
  4. 4 Leverage native connectors between Azure Databricks and Azure Synapse Analytics to access and move data at scale.
  5. 5 Power users take advantage of the inbuilt capabilities of Azure Databricks to perform root cause determination and raw data analysis.
  6. 6 Run ad hoc queries directly on data within Azure Databricks.
  7. 7 Take the insights from Azure Databricks to Cosmos DB to make them accessible through web and mobile apps.
Analyses en temps réelExtrayez des informations de données de streaming en direct en toute facilité. Capturez des données en continu à partir de n’importe quel appareil IoT ou de journaux de parcours de visite de site web, et traitez-les en temps quasi réel.12345678
  1. Overview
  2. Flow

Real-time analytics

Overview

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

Flow

  1. 1 Easily ingest live streaming data for an application using Apache Kafka cluster in Azure HDInsight.
  2. 2 Bring together all your structured data using Azure Data Factory to Azure Blob Storage.
  3. 3 Take advantage of Azure Databricks to clean, transform and analyse the streaming data, and combine it with structured data from operational databases or data warehouses.
  4. 4 Use scalable machine learning/deep learning techniques to derive deeper insights from this data using Python, R or Scala, with inbuilt notebook experiences in Azure Databricks.
  5. 5 Leverage native connectors between Azure Databricks and Azure Synapse Analytics to access and move data at scale.
  6. 6 Build analytical dashboards and embedded reports on top of Azure Data Warehouse to share insights within your organisation and use Azure Analysis Services to serve this data to thousands of users.
  7. 7 Power users take advantage of the inbuilt capabilities of Azure Databricks and Azure HDInsight to perform root cause determination and raw data analysis.
  8. 8 Take the insights from Azure Databricks to Cosmos DB to make them accessible through real-time apps.
Analyse à l'échelle du cloud avec Discovery HubUtilisez Discovery Hub pour définir un domaine de données à l'aide d'une interface graphique utilisateur, en bénéficiant des définitions stockées dans un référentiel de métadonnées. Le code de création du domaine de données est généré automatiquement tout en restant entièrement personnalisable. L'entrepôt de données moderne qui en résulte est prêt à prendre en charge l'analyse à l'échelle du cloud et l'intelligence artificielle.