Are you planning a migrating of your data platform to Azure Synapse Analytics? Is it currently based on Azure Databricks, Azure Data Factory, and Azure Data Lake Storage? Make sure to grab these 10 tips! We'll talk about Spark compatibilities, orchestration pitfalls and solution deployment differences.
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This session will walk you through three different ways to set up an affordable Azure based Data Warehouse solution. Covering pros and cons with each of the architectures.
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Overview to some of the more popular Azure Data Engineering services used to analyze data
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I will show a few challenges while deploying Azure Data Factory and solution for them.
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Welcome to Azure DevOps trio, a tale about how a development team and an operations team have to bond together and start using Azure DevOps for Data Platform deployments.
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Introductory view into Azure Synapse Analytics
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A intro session showing the whys, how's and what's for building a Data Lakehouse in Azure Synapse Analytics
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We'll explore delivering this framework within an enterprise and consider an architect’s perspective on a wider platform of ingestion/transformation workloads with multiple batches and execution stages.
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This data governance session guides you through the organization processes, policies and roles that are required for a successful data governance adoption. In addition to demos showing the possibilities of Azure Purview (the MS data governance service), we will share about experiences from our data governance workshops and adoption projects with our customers.
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I'll explain the current popular data architectures: Data Lakehouse, Data Mesh, and Data Fabric
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Session covering table distributions, partitioning , RSC and materialised views.
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DW Automation and Design Best Practices
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Reality Check on Microsofts Enterprise Scale Analytics Framework
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A tale about how a development team and an operations team must bond together and figure out how to use GitHub and Azure DevOps together for Data Platform deployments.
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Tips and tricks for getting the best performance out of Spark SQL on Synapse Analytics while keeping costs under control.
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A look at the features and uses of Synapse Analytics Data Explorer Pools
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Hybrid Transactional Analytical Processing solve the age old problem of integrating operational processes with analytical capabilities within a single system. Find out what they're and how they deliver value
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Learn how to easily build your lake database without having to start with a blank canvas on Azure Synapse.
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What happens when you mix one rapidly-changing startup, one data analyst, one data engineer, and one hypothesis that Azure Synapse Analytics could be the right tool of choice?
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There is a lot of content available on Synapse for Data Engineering, but what about Machine Learning? In this session we will look at how to integrate a SparkML model in Synapse.
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