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 135: Seinfeld Episode
Episode 134: CosmosDB
Episode 133: Shrinking Files
Episode 132: What technologists can learn from superheroes
Episode 131: Big Data Solutions in the Cloud
Episode 130: Use Case for PowerShell
Episode 129: Graph Databases
Episode 128: Database Doing DevOps
Episode 127: Developing in the database
Episode 126: SQLSaturday Edition
Episode 125: You must be an engineer
Episode 124: Beyond the runbook; DR Organization
Episode 123: Top 5 things to know when getting admin access
Episode 122: Isolation Levels
Episode 121: What makes a good manager?
Episode 120: SQL Injection
Episode 119: Getting started with GitHub
Episode 118: How has index maintenance changed?
Episode 117: PASS Summit Retrospective
Episode 116: Are people still using PSSDiag?
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