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 255: Automate Complex CRUD with sp_CRUDGen
Episode 254: Code Smell Checks with sp_Develop
Episode 253: Go Mobile with Power Apps
Episode 252: The Cumulative Update Dilemma
Episode 251: Azure Cognitive Services
Episode 250: What happens before... “COMPANEROS!”
Episode 249: Data Marts in Power BI
Episode 248: Inventory Documentation
Episode 247: Pushing the Boundaries or Pushing Your Luck
Episode 246: Microsoft Build 2022 Announcements
Episode 245: Tooling Updates
Episode 244: Extended Events vs SQL Server Audit
Episode 243: Choosing What Content To Focus On
Episode 242: Upgrading Your SQL Server
Episode 241: Replicating Data with Azure SQL Data Sync
Episode 240: Azure Synapse Link
Episode 239: Bi-directional HA/DR to Azure SQL
Episode 238: Getting Started with Power BI - Part 2
Episode 237: Getting Started with Power BI - Part 1
Episode 236: Database Monitoring with SQL Sentry
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