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Mark Pryce-Maher
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Sessions & Content
Mark Pryce-Maher is a Senior Program Manager on the Azure Synapse Analytics Customer Success Engineering team at Microsoft, where he is working with customers implementing Enterprise Data Platforms.
Sessions
Previous Sessions
Building a SSMS Add-in; The Agony and Ecstasy
We will travel back in time a bit to SQL 2005 to see how SSMS Add-ins worked, then jump forward to the present day were we will go through the process of writing a SSMS Add-in for R2.
Azure Machine Learning from the ground up
Azure Machine Learning is a fully managed cloud service for predictive analytics. In this 1hour session, we will run through; ML Studio,using data, Creating and running Experiments, visualising results, R , publishing and using experiments.
Microsoft Premier Field Engineers and Consultants Unplugged.
This session is your opportunity to ask the people who know, the questions you want to ask. Microsoft Premier Field Engineers and Consultants are the people that go out to talk to customers and implement solutions.
Azure Synapse Analytics: Evolving Azure SQL Data Warehouse
In this session we explore Azure Synapse Analytics, we will dive into this limitless analytics service and explore how it brings together enterprise data warehousing and Big Data analytics.
Modernizing & Migrating Your Data Warehouse w/ Azure Synapse
This session will dive into how to successfully migrate to Azure Synapse, all the way from code conversion to enterprise grade developer tooling, with real customer examples for product and migration experts.
Azure Synapse Analytics: Evolving Azure SQL Data Warehouse
In this session we explore Azure Synapse Analytics, we will dive into this limitless analytics service and explore how it brings together enterprise data warehousing and Big Data analytics.
Dedicated SQL Pools : How some stuff 'really' works
Session covering table distributions, partitioning , RSC and materialised views.
Monster Data Loading with Synapse
Get to grips with data loading in Synapse.
Reporting on 1.4B rows with Serverless SQL Pools
Building a dashboard using Serverless SQL Pools in a performant way