Analytics

We have heard from our customers that investigating malicious activity on their systems can be tedious and knowing where to start is challenging.

With Azure Data Factory (ADF) visual tools, we listened to your feedback and enabled a rich, interactive visual authoring and monitoring experience. It allows you to iteratively create, configure, test, deploy and monitor data integration pipelines without any friction.

Azure Stream Analytics is a serverless PaaS service in Azure to run real-time analytics on fast moving streams of data. Today, we are excited to announce several new features in Azure Stream Analytics.

Data is transformative. The ability to turn data into breakthrough insights is foundational to remain relevant in an increasingly competitive market.

Secure credential management is essential to protect data in the cloud.

Core Services Engineering (formerly Microsoft IT) shows how we use subscriptions and resource groups within our enterprise Azure footprint for control and security while still allowing developers to go fast.

We are pleased to announce Azure Analysis Services now provides integration with cloud data sources residing on Azure Virtual Networks (VNets). Organizations use VNets for enhanced security and isolation.

There is increasingly a need among users to develop and debug their Extract Transform/Load (ETL) and Extract Load/Transform (ELT) workflows iteratively. Now, Azure Data Factory (ADF) visual tools allow you to do iterative development and debugging.

Data science and machine learning can be applied to solve many common business scenarios, yet there are many barriers preventing organizations from adopting them.

Azure Data Factory (ADF) visual tools public preview was announced on January 16, 2018. With visual tools, you can iteratively build, debug, deploy, operationalize and monitor your big data pipelines.

Azure Databricks general availability was announced on March 22, 2018. Now Azure Databricks is fully integrated with Azure Data Factory (ADF).

To help our customers with their adoption of Azure services for big data and data warehousing workloads we have identified some common adoption patterns which are reference architectures for…