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 235: SQL Trail 2021 In-person Q&A
Episode 234: Communication Tips for the IT Pro
Episode 233: ScriptDOM
Episode 232: Giving Technical Presentations
Episode 231: Mental Health and Wellness in IT
Episode 230: RTO & RPO
Episode 229: Data Migration Assistant
Episode 228: Predicting Application Problems with Database Metrics
Episode 227: SSDT Methodologies for DB DevOps
Episode 226: SQL Server IaaS Agent Extension
Episode 225: Dashboard Design Principles
Episode 224: The Standup Meeting
Episode 223: Podcast Update
Episode 222: Azure Arc-enabled Data Services
Episode 221: SQL Trail March 2021 Retrospective
Episode 220: Microsoft Ignite Recap
Episode 219: SQL Server Inventory
Episode 218: File Growths
Episode 217: A Little Something About A Few Things
Episode 216: EDI vs ETL
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