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 216: EDI vs ETL
Episode 215: Azure Data Factory
Episode 213: New Goals for 2021
Episode 212: 10 Things You Need to Know About Data Security
Episode 211: Solorigate
Episode 210: The Elephant in the Room
Episode 209: Career Ready: Advice to New Graduates
Episode 208: SQL Server and Graph Data
Episode 207: SQL Trail 2020 Retrospective
Episode 206: .NET Core Interactions with SQL Server
Episode 205: Data Modeling for Power BI
Episode 204: IoT in Azure
Episode 203: Spark in Action
Episode 202: Virtual Conferences
Episode 201: Common Data Model
Episode 200: Anything but the Cowboys . . .
Episode 199: Technical Debt
Episode 198: Cloud Infrastructure
Episode 197: Power Query in Power BI
Episode 196: Teleworking
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