Duration: 60 minutes
Track: BI Platform Architecture, Development & Administration
Companies are looking for the existing data to provide answers for many questions and Azure Machine Learning [ML] can help provide them. Starting with data stored in a SQL Server database deployed in Azure, attendees will learn rules to classify the data for ML analysis. Building upon this information, I’ll show the best methods for determining which ML models to use as well as how to integrate custom analysis methods. The presentation will cover the ability to expand ML by including analysis components from other sources by incorporating existing modules from both custom R code and SQL scripts within the ML solution. Upon completion, the ML experiment will be deployed as part of a Data Factory pipeline, as it is the tool for distributing ML, and lastly added back to the Azure SQL server database. Join this session to learn more about the opportunities for data analysis using Azure ML, and see how the insights gained can be included in your current data distribution and visualizations.
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Business Intelligence Consultant, Pragmatic Works
Ginger Grant has worked with the Microsoft BI stack for many years, for a number of industries including transportation, education, insurance, and healthcare. An active member of the Microsoft data... View More