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!
Moving up the ranks in the holy technology wars is the medallion architecture, and boy are we interested in getting your thoughts. Not since the 2008 Olympics and Michael Phelps' tenth of a second win over Milorad Cavic has there been so much controversy around bronze, silver, and gold.
This episode of the podcast has a genesis with Databricks and the methodology of getting data into a workable form for all the reporting pieces businesses love so much. We discuss our thoughts on the various layers of a medallion architecture and the implementation in Azure delta lake environments.
Have a different take? Let us know!
The show notes for today's episode can be found at Episode 270: Medallion Architecture. Have fun on the SQL Trail!
We love hearing from our listeners!!! In this episode, a long-time listener asked about the future of AI in the data platform space. We thought this was a very interesting topic as Microsoft has been including Artificial Intelligence or AI in more and more of its marketing material. In this episode we'll dive into the definition of AI, what features are currently available, how we can leverage those technologies, and where we think this might go in the future. One of the challenges we currently face is all the buzz and excitement around AI. From a data platform vantage point, we started with analytics and training models to analyze the data. Microsoft has suddenly slapped Artificial Intelligence on some of the feature sets and confuses the issue a bit.
We are excited to have Mike Chrestensen from Duke Health as our episode guest to help us sort it all out. Mike has begun leveraging AI in his work and I think he gives some interesting thoughts on how he has used it to help his team go faster. We hope you enjoy the episode. As always, we welcome your feedback and thoughts.
The show notes for today's episode can be found at Episode 268: AI and the Future of the DBA. Have fun on the SQL Trail!
All your data, all your teams—in one place. What am I? If you said Microsoft Fabric, you win! When I interned with Cisco Systems in 2000, I supported a platform called Unified Messaging. At that time, we were talking about getting your email, voice mail, and faxes all in one place. My, how the times have changed.
To a certain extent, the Microsoft Fabric is an extension, or wrapper, of some of the tools we have talked about in other episodes. The central idea is the ability to store your information in a data lake, and then having multiple tools at your disposal to use that data as required by the business. Power BI is the cherry on top - providing the visualizations and access to the source data that the business users like to get their hands on.
In this episode we talk through the architecture and then discuss when organizations might want to adopt Microsoft Fabric. Would you like to hear more about this in a future episode? Let us know and we’ll look to circle back with long time friend of the podcast Jonathan Stewart.
The show notes for today's episode can be found at Episode 267: Microsoft Fabric. Have fun on the SQL Trail!