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5 Mistakes in Cloud Data Migration
We're fortunate in seeing tons of customers migrate to the cloud - this session covers major
A Distributed Availability Groups Primer
A distributed availability group is not your mother's availability group. Want to know more? Attend this session.
Advanced analytics features in Power BI
In this session you’ll learn about some of these advanced analytical features in Power BI, including: the Analytics pane on visuals; the Key Influencers visual and other AI features.
An administrators guide to SQL Server 2019 BDC
Join this session if you are interested in the administration scenarios of the big data clusters, including tooling for monitoring, how to deploy and secure the environment, and to learn about the latest improvements.
An introduction to Azure Synapse Analytics!
Azure Synapse Analytics combines the power of Data Lakes with Data Warehouses, empowering the organizations to build Big Data, Advanced Analytics and Business Intelligence in one single platform.
Analysis Services DevOps with Tabular Editor
Continuous Integration and Delivery can be a pickle for Analysis Services Tabular Models when using the standard tools. With Azure DevOps, GIT and Tabular Editor, there's a better way...
App Modernization & Migration using migr tools & Azure SQL
In this session, you'll learn about an end-to-end scenario that takes customers through the application migration process, and how that relates to the data migration.
Application and Database Migrations-A Pester Journey
Application and Database migrations can be a cause for concern. How many times have you heard, "If it isn't broke don't fix it". Come see how you can give confidence to key stake holders on testing the process.
Applying DevOps practices to Machine Learning
When buzzwords like DevOps and Machine Learning collide, you need a demo and talk that shows how to actually increase the delivery speed of Advanced Analytics solutions.
Artificial Intelligence, Machine Learning and Deep Learning
What is the difference between Artificial Intelligence, Machine Learning and Deep Learning and how can each be used? Join Buck Woody cover simple, clear explanations for these technologies, how they can be applied.
Automated Machine Learning, the good, the bad and the why
Automated Machine Learning, "1 button data science", has been with us for a while. As always there's fans and detractors. We'll discuss when and why you'd use AutoML and when it's better to avoid it.
Azure AI, Power new possibilities for every organization
AI and data is at the center of the digital feedback loops. We have invested in a comprehensive portfolio of AI tools, infrastructure and services. Come to this session to get an update of Azure AI with demos.
Azure data services on Azure Arc
In this session you’ll learn more about Azure data services on Azure Arc
Azure Key Vault, Azure Dev Ops and Data Factory
Azure Key Vault, Azure Dev Ops and Data Factory how do these Azure Services work perfectly together!
Azure Kubernetes and Istio: Data Science in Production
How do you deploy multiple machine learning models in production to solve your challenge? How do enable canary releases and A/B testing? How do you make sure a user is always served by the same version of the model?
Azure Machine Learning and the Python SDK
Understand how to create, train and operationalize your data science projects in Azure Machine Learning.
Azure SQL Database Edge-Optimized SQL Engine for Edge/IoT
Azure SQL Database Edge has taken the same SQL database engine and optimized it for the Edge.This session explores customer implementations with Azure SQL Database Edge, along with new product features.
Azure Synapse Analytics
Learn all about Azure Synapse Analytics, including demos so you can see exactly how it works and how it can make your life easier.
Baselining Performance with DEA
Learn what the Database Experimentation Advisor is and how you can start using it to baseline performance from a target and source server when new changes are introduced.
Big Data Processing with .NET and Spark
Come learn how to use .NET and Spark together in Azure Synapse and elsewhere to cook and analyze your data!
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