In the rapidly evolving world of AI, keeping up with the latest tools and technologies can feel like a full-time job. One of the most exciting recent releases from Microsoft is the introduction of AI Skills in Microsoft Fabric. With the potential to streamline operations, boost productivity, and even change the way we work, this … Continue reading Microsoft Fabric AI Skills vs. Copilot: Which GenAI Gives You the Best Answers?
Category: LLM
What???!!!??? Forecasting with LLM and GenAI!
https://youtu.be/2G4WUV81ExI Today, we're tackling a topic you probably haven't seen before: how to forecast and make predictions in Microsoft Fabric using Generative AI and Large Language Models (LLMs). While most videos focus on LLMs as assistants or copilots, I find that use case uninspiring and soon-to-be commoditized. Instead, I'm focused on logic intelligence—applying GenAI to … Continue reading What???!!!??? Forecasting with LLM and GenAI!
LLM and GenAI in Fabric, no Azure required!
In this video, we’re taking our RAG architecture to intergalactic levels! Building on our previous video (https://youtu.be/oCHinlZRsLU), we’re removing dependencies on PaaS components like Document Intelligence and Azure AI Search. Instead, we’re leveraging LangChain to process PDF documents and using the open-source vector database, Chroma DB, as our vector store. https://youtu.be/jwVOQCUUH1Y this is the relevant … Continue reading LLM and GenAI in Fabric, no Azure required!
Will Copilot in PowerBI Desktop ever be able to help you?
Who is going to win in the upcoming AI vendors showdown? My guess is it will be whoever can figure out how to make AI understand the intricacies of various business domains, like sales and supply chain, for example. So this is the context that I use to understand the effectiveness and usefulness of #Copilots in #PowerBI and #MSFabric. How good is it, and how would we know? Who is it built for? These are some of the questions that I am trying to tackle in this video.
Are we at the tipping point?
Are you STILL one of the people who have not yet realized that the world of BI is about to get turned upside down with GenAI and LLMs? Well, you can keep basking in your ignorance, but for the rest of us, we need to figure out how to stay ahead of where this is going and how to not be left behind. With my latest video/tutorial, we're stepping into the future with LangChain LLM Agents, and how they're revolutionizing the way we interact with Power BI semantic models within Microsoft Fabric. Forget the traditional ways of data processing and get ready for a mind-blowing journey into AI-driven analytics. You can query your Power BI datasets/semantic models and potentially replace lines of code with just a few simple prompts. hashtag#azure hashtag#OpenAI hashtag#LangChain hashtag#PowerBI hashtag#MicrosoftFabric hashtag#AI hashtag#BusinessIntelligence hashtag#Innovation hashtag#BI hashtag#datascience hashtag#obvience hashtag#getsmartertogether
How to generate Business Friendly #PowerBI Data Dictionary using #OpenAI #SemanticLink #msfabric
Learn how to generate a business-friendly PowerBI data dictionary using OpenAI, SemanticLink, and MSFabric! In this video, we explore how to incorporate Azure OpenAI into the world of Business Intelligence and Microsoft Fabric. We use the Semantic Link library to create our data dictionary. Then we enrich it using Azure OpenAI to derive business audience-friendly descriptions from our DAX measure definitions. Check out the video to learn more! hashtag#PowerBI hashtag#OpenAI hashtag#SemanticLink hashtag#MSFabric
Game Changer: Enrich Your Data with Azure OpenAI LLM in a Microsoft Fabric Notebook
Dive into the world of Azure OpenAI and its groundbreaking impact on data engineering. This post explores the cutting-edge applications of large language models (LLMs) for data enrichment, offering a deep dive into practical use cases that underscore the transformative potential of Azure OpenAI in the field. If you're poised to elevate your data strategies and harness the power of LLMs, this essential read is your gateway to the future of data engineering.
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