Azure Machine Learning is a platform for developing and deploying your machine learning models on Azure. We will look at the life cycle of ML projects: from data, to model, to consumption. This will include Automated Machine Learning capabilities.
Deploying untested code to production isn't ideal, manual testing can be slow and unreliable. In this talk we will look at the different types of automated testing we can use for our databases to give us confidence in the quality of the code.
This session focuses on the deeper integration of SQL Server Integration Services (SSIS) in Azure Data Factory (ADF) and the broad extensibility of Azure-SSIS Integration Runtime (IR).
Many organisations using Power BI seek the Nirvana of self-serve and enterprise reporting, but are left with an unstructured governance strategy. This session simplifies the governance process, by utilising Microsoft Flow and Power BI together.
Step back through the ages and explore how database teams have approached creating environments for dev and test. Learn how, in the new age of provisioning, databases are delivered safer, faster, and more efficiently
Azure introduces a range of new services for transaction processing and analytics solutions which mean we don’t need to deploy virtual machines. This session provides insight into how we see customers deploying evergreen and futureproof solutions.
Learn how Machine Learning Services in SQL Server is a powerful end-to-end ML platform for customers, on both Windows and Linux. Come learn about the unique value proposition of doing your entire machine learning pipeline in-database – right from data pre-processing, feature engineering, and model training to deploying ML models and scripts to production in secure and compliant environment without moving data out. 
Learn about how to future-proof your modern data warehousing environment to meet the needs of the business for the long term; as well as how to overcome common data warehousing challenges, the related must-have technology solution.
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