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Power BI Machine Learning and OpenAI

You're reading from   Power BI Machine Learning and OpenAI Explore data through business intelligence, predictive analytics, and text generation

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781837636150
Length 308 pages
Edition 1st Edition
Languages
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Author (1):
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Greg Beaumont Greg Beaumont
Author Profile Icon Greg Beaumont
Greg Beaumont
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Data Exploration and Preparation
2. Chapter 1: Requirements, Data Modeling, and Planning FREE CHAPTER 3. Chapter 2: Preparing and Ingesting Data with Power Query 4. Chapter 3: Exploring Data Using Power BI and Creating a Semantic Model 5. Chapter 4: Model Data for Machine Learning in Power BI 6. Part 2: Artificial Intelligence and Machine Learning Visuals and Publishing to the Power BI Service
7. Chapter 5: Discovering Features Using Analytics and AI Visuals 8. Chapter 6: Discovering New Features Using R and Python Visuals 9. Chapter 7: Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service 10. Part 3: Machine Learning in Power BI
11. Chapter 8: Building Machine Learning Models with Power BI 12. Chapter 9: Evaluating Trained and Tested ML Models 13. Chapter 10: Iterating Power BI ML models 14. Chapter 11: Applying Power BI ML Models 15. Part 4: Integrating OpenAI with Power BI
16. Chapter 12: Use Cases for OpenAI 17. Chapter 13: Using OpenAI and Azure OpenAI in Power BI Dataflows 18. Chapter 14: Project Review and Looking Forward 19. Index 20. 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.

You have been reading a chapter from
Power BI Machine Learning and OpenAI
Published in: May 2023
Publisher: Packt
ISBN-13: 9781837636150
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