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9
Azure Machine Learning: Applying Software Engineering to ML
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.
Azure Managed Instances—Your Bridge to the Cloud
Managed Instances can make your cloud migrations simpler, but have their own nuances. Learn about what you need to know to manage this new platform.
DB Engineering: Shall we test the code before we hit prod?
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.
Deeper Integration and New Transformation for SSIS in ADF
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).
Developing SQL Server code to keep your DBA happy
In this hour long session we will attempt to include lots of advice and guidance on how to develop code that will easily get approved by your DBA prior to release to production.
Implementing a CI/CD pipeline for Anomaly Detection and Predictive Maintenance on Azure
Implementaing a CI/CD pipeline for Anomaly Detection and Predictive Maintenance on Azure
SentryOne Tools for Productivity and Performance
This quick vendor session demonstrates the spectrum of SentryOne's best-of-breed products for the Microsoft Data Platform, from Task Factory, to Plan Explorer, to DOC xPress, to the SentryOne monitoring platform, and beyond.
Share Your Story: Developing Your First Presentation
Take an idea and learn how to develop your first session.
Smart Alerts in SQL DB using Automation and Logic Apps
Learn how to make Azure do the work for you by developing smart responses for Azure SQL DB alerts using Automation and Logic Apps.
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