Cloud scale analytics with Discovery Hub

Use Discovery Hub to define a data estate using a graphical user interface, with definitions stored in a metadata repository. Code for building the data estate is generated automatically while remaining fully customizable. The resulting modern data warehouse is ready to support cloud scale analytics and AI.

Cloud scale analytics with Discovery HubUse Discovery Hub to define a data estate using a graphical user interface, with definitions stored in a metadata repository. Code for building the data estate is generated automatically while remaining fully customizable. The resulting modern data warehouse is ready to support cloud scale analytics and AI.12345

Combine all your structured and semi-structured data in Azure Data Lake Storage using Discovery Hub’s data engineering pipeline with hundreds of native data connectors.

Clean and transform data using the powerful analytics and computational ability of Azure Databricks.

Move cleansed and transformed data to Azure SQL Data Warehouse, creating one hub for all your data. Take advantage of native connectors between Azure Databricks (Polybase) and Azure SQL Data Warehouse to access and move data at scale.

Build operational reports and analytical dashboards on top of SQL Database to derive insights from the data and use Azure Analysis Services to serve the data.

Run ad-hoc queries directly on data within Azure Databricks.

  1. 1 Combine all your structured and semi-structured data in Azure Data Lake Storage using Discovery Hub’s data engineering pipeline with hundreds of native data connectors.
  2. 2 Clean and transform data using the powerful analytics and computational ability of Azure Databricks.
  3. 3 Move cleansed and transformed data to Azure SQL Data Warehouse, creating one hub for all your data. Take advantage of native connectors between Azure Databricks (Polybase) and Azure SQL Data Warehouse to access and move data at scale.
  1. 4 Build operational reports and analytical dashboards on top of SQL Database to derive insights from the data and use Azure Analysis Services to serve the data.
  2. 5 Run ad-hoc queries directly on data within Azure Databricks.

Implementation guidance

Products/Description Documentation

Azure Data Lake Storage

Massively scalable, secure data lake functionality built on Azure Blob Storage

Azure Databricks

Fast, easy, and collaborative Apache Spark-based analytics platform

SQL Data Warehouse

Elastic data warehouse as a service with enterprise-class features

Azure Analysis Services

Enterprise-grade analytics engine as a service

Power BI Embedded

Embed fully interactive, stunning data visualizations in your applications