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 115: The Companero Conference Retrospective
Episode 114: How do you start consulting?
Episode 113: Standing on the shoulders of giants
Episode 112: Keeping up with patching
Episode 111: How do you prepare for conferences?
Episode 110 How do I build trust with my team
Episode 109: To certify or not to certify?
Episode 108: The Future of the Relational Database
Episode 107 BI for the Little Guy
Episode 106 Temporal Tables
Episode 105 When is enough, enough?
Episode 104: Keeping up with technology
Episode 103 Plan Reuse
Episode 102 Monitoring Availability Groups
Episode 101 Inspecting a new Database
Episode 100 Role Reversal
Episode 99 Imposter Syndrome
Episode 98: The first change you make
Episode 97 Transactional Replication
Epsiode 96 Building Community Tools
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