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Power BI Machine Learning and OpenAI

You're reading from  Power BI Machine Learning and OpenAI

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781837636150
Pages 308 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Greg Beaumont Greg Beaumont
Profile icon Greg Beaumont
LinkedIn
Greg Beaumont is a data architect at Microsoft, where he enjoys identifying and solving complex problems backed by his experience in data architecture and a passion for innovation. Focusing on the healthcare industry, Greg works closely with customers to plan enterprise analytics strategies, evaluate new tools and products, conduct training sessions and hackathons, and architect solutions that improve the quality of care and reduce costs. He strives to be a trusted advisor to his customers and is always seeking new ways to drive progress and help organizations thrive. He is a veteran of the Microsoft data speaker network and has worked with hundreds of customers on their data management and analytics strategies.
See other products by Greg Beaumont

Table of Contents (21) Chapters

Preface Part 1: Data Exploration and Preparation
Chapter 1: Requirements, Data Modeling, and Planning Chapter 2: Preparing and Ingesting Data with Power Query Chapter 3: Exploring Data Using Power BI and Creating a Semantic Model Chapter 4: Model Data for Machine Learning in Power BI Part 2: Artificial Intelligence and Machine Learning Visuals and Publishing to the Power BI Service
Chapter 5: Discovering Features Using Analytics and AI Visuals Chapter 6: Discovering New Features Using R and Python Visuals Chapter 7: Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service Part 3: Machine Learning in Power BI
Chapter 8: Building Machine Learning Models with Power BI Chapter 9: Evaluating Trained and Tested ML Models Chapter 10: Iterating Power BI ML models Chapter 11: Applying Power BI ML Models Part 4: Integrating OpenAI with Power BI
Chapter 12: Use Cases for OpenAI Chapter 13: Using OpenAI and Azure OpenAI in Power BI Dataflows Chapter 14: Project Review and Looking Forward Index Other Books You May Enjoy

Summary

In this chapter, you explored the data available for your project and reviewed subsequent options for mapping data to the requirements of your stakeholders. You reviewed data architecture options to meet both business intelligence and ML requirements in Power BI and decided upon a hybrid approach that blends a star schema design with flattened data. You also formulated a plan to explore, analyze, design, build, and deploy your solution. Finally, you decided upon three use cases for predictive ML models in Power BI.

In the next chapter, you will ingest and prep data from the FAA Wildlife Strike database using Power Query within Power BI. You’ll deep dive into data characteristics, decide what is needed for your design, and build out a flexible foundation that will support both the current project and future iterations and changes. Your approach in Power Query will support both business intelligence analytics in Power BI and predictive analytics in Power BI ML.

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Power BI Machine Learning and OpenAI
Published in: May 2023 Publisher: Packt ISBN-13: 9781837636150
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Authors (1)

Profile icon Greg Beaumont
LinkedIn
Greg Beaumont is a data architect at Microsoft, where he enjoys identifying and solving complex problems backed by his experience in data architecture and a passion for innovation. Focusing on the healthcare industry, Greg works closely with customers to plan enterprise analytics strategies, evaluate new tools and products, conduct training sessions and hackathons, and architect solutions that improve the quality of care and reduce costs. He strives to be a trusted advisor to his customers and is always seeking new ways to drive progress and help organizations thrive. He is a veteran of the Microsoft data speaker network and has worked with hundreds of customers on their data management and analytics strategies.
Read more
See other products by Greg Beaumont

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