What kinds of problems are organizations solving with Machine Learning? In this episode, we explore a situation where a public works department was looking for more accurate information to predict future water levels based on rainfall to maintain water tank storage for balancing pressure and to prevent overflow flooding. Marathon data solutions consultants Brian Knox and Andy Yao, built a custom machine learning model and made the results available through Power BI reporting. We talk through some of the data hurdles the project presented, the tools they used, and how their work provided results the client could rely on. We touch on Azure ML environment and future integrations that will come with Power BI and ML.
Have you done any work in ML or predictive modeling? Did you get any good take-aways from today's podcast? Leave us some love ❤️ on LinkedIn, Twitter/X, Facebook, or Instagram.
The show notes for today's episode can be found at Episode 275: Machine Learning and Power BI. Have fun on the SQL Trail!
Episode 155: Data Science
Episode 154: Test Driven Development
Episode 153: SQL Trail 2018 Retrospective
Episode 152: Do you use Analysis Services?
Episode 151: Azure SQL Database Managed Instance
Episode 150: The SQL Data Partners Team
Episode 149: Managing lots of databases
Episode 148: High Performance SSRS
Episode 147: Always Encrypted
Episode 146: SQL Trail Speakers
Episode 145: Is SSIS still relevant? Part 2
Episode 144: Is SSIS still relevant? Part 1
Episode 143: Transitioning from DBA to Data Warehouse Architect
Episode 142: Do You Have a HEAP of Hurting?
Episode 141: Wait, Wait, What?
Episode 140: Why data types matter
Episode 139: Getting Started with SQL Server in Azure
Episode 138: Meeting of the Minds
Episode 137: You want to work with Analytics?
Episode 136: Devops with Visual Studio
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