西格玛计算:如何在 Sigma 中使用输入表改进 Databricks 中的数据科学和机器学习应用程序.pdf

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西格玛计算:如何在 Sigma 中使用输入表改进 Databricks 中的数据科学和机器学习应用程序.pdf

1、Sigma+DatabricksHow using Sigma Input Tables improves Data Science and Machine Learning within Databricks Databricks2023Introduction:SpeakersMitch is an experienced data analytics professional with a 12-year tenure in both managerial and individual contributor roles.Before joining Sigma,Mitch spent

2、the 3 prior years running data teams on Databricks.Mitch ErtlePartner Solutions Engineer,DGreg is a software engineer,chocolatier,and former synthetic biologist with a background in distributed systems.Greg leads the input tables project at Sigma.Prior to Sigma,he spent 4 years at Databricks working

3、 in both the platform and Databricks Runtime orgs.Greg OwenStaff Software EIn this lightning talk,we will cover1How Sigma provides a single pane of glass into your Lakehouse2Highlight the benefits of Input Tables,how they can improve your Databricks ML and analytics workflows3Demonstrate how organiz

4、ations can use Sigma+Databricks together to unlock ML models by using Input Tables.Using SigmaFor real-time data analysis and insightsExploratory Layer of the Modern Data StackUnlimited Ad Hoc Exploration to address unpredictable requirementsEnables teams to do their jobs backed by dataAugment Legac

5、y Solution GapsUsing SigmaWith Input TablesWhat are they?Write data to your lakehouse as easily as typing into a spreadsheetInput tables allow users to:Perform scenario modeling&what/if analysis on live dataComplete their analysis when data is missing in the warehouseMake analysis actionable by capt

6、uring business context against live analysisBetter TogetherDatabricks+SigmaLive ConnectionSecured+Governed Data Warehousing Data Science&ML Workflows&Streaming Unity Catalog Embedded Internal Analytics Input Tables Sigma AI DemoIn this ligh

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