Learn the latest integration in Azure Data Factory with Azure Data Lake Storage Gen2 and Azure Data Explorer which enables you to meet the advanced needs of your analytics workloads by leveraging these services.
Cloud data integration helps organizations integrate data of various forms and unify complex processes in a hybrid data environment. A number of times different organizations have similar data integration needs and require repeat business processes.
Azure Functions is a serverless compute service that enables you to run code on-demand without having to explicitly provision or manage infrastructure. Using Azure Functions, you can run a script or piece of code in response to a variety of events.
The Integration Runtime (IR) is the compute infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments. If you need to perform data…
GitHub is a development platform that allows you to host and review code, manage projects and build software alongside millions of other developers from open source to business. Azure Data Factory (…
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.
Continuing our series of tutorials on SaaS application patterns with SQL Database, we are delighted to announce an additional cross tenant analytics tutorial.
Secure credential management is essential to protect data in the cloud. With Azure Key Vault, you can encrypt keys and small secrets like passwords that use keys stored in hardware security modules (…
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 Data Factory added more new features in July, including Preview for Data Management Gateway high availability and scalability, fault tolerance feature of skipping or logging incompatible rows during copy, and authentication support of using Service Principal to access Azure Data Lake Analytics.