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AI and Business Rule Engines for Excel Power Users

You're reading from   AI and Business Rule Engines for Excel Power Users Capture and scale your business knowledge into the cloud – with Microsoft 365, Decision Models, and AI tools from IBM and Red Hat

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781804619544
Length 386 pages
Edition 1st Edition
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Authors (2):
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Paul Browne (GBP) Paul Browne (GBP)
Author Profile Icon Paul Browne (GBP)
Paul Browne (GBP)
ALEX PORCELLI ALEX PORCELLI
Author Profile Icon ALEX PORCELLI
ALEX PORCELLI
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1:The Problem with Excel, and Why Rule-Based AI Can Be the Solution FREE CHAPTER
2. Chapter 1: Wrestling with Excel? You Are Not Alone 3. Chapter 2: Choosing an AI and Business Rules Engine – Why Drools and KIE? 4. Chapter 3: Your First Business Rule with the Online KIE Sandbox 5. Part 2: Writing Business Rules and Decision Models – with Real-Life Examples
6. Chapter 4: More Decision Models, Business Rules, and Decision Tables 7. Chapter 5: Sharing and Deploying Decision Models Using OpenShift and GitHub 8. Chapter 6: Calling Business Rules from Excel Using Power Query 9. Part 3: Extending Excel, Decision Models, and Business Process Automation into a Complete Enterprise Solution
10. Chapter 7: Using Business Rules in Excel with Visual Basic, Script Lab, or Office Scripts 11. Chapter 8: Using AI and Decision Services Within Power Automate Workflows 12. Chapter 9: Advanced Expressions, Decision Models, and Testing 13. Part 4: Next Steps in AI, Machine Learning, and Rule Engines
14. Chapter 10: Scaling Rules in Business Central with Docker and the Cloud 15. Chapter 11: Rules-Based AI and Machine Learning AI – Combining the Best of Both 16. Chapter 12: What Next? A Look inside Neural Networks, Enterprise Projects, Advanced Rules, and the Rule Engine 17. Index 18. Other Books You May Enjoy Appendix A - Introduction to Visual Basic for Applications 1. Appendix B - Testing Using VSCode, Azure, and GitHub Codespaces 2. Appendix C - Troubleshooting Docker

DMN and FEEL expressions – extending what you know

As we worked through Chapters 3 and 4, we covered many of the key points of the FEEL expression language:

  • We saw that FEEL allows you to write boxed expressions (like what you type into the Excel formula box). There are many different places that you can use FEEL expressions – from decision nodes to lists to decision tables.
  • One sort of FEEL expression was text and string manipulation – we used it to create a Hello [your name] example. If you’ve read the reference docs, you’ll have seen that most text functions in Excel have an equivalent in FEEL. This includes converting strings into uppercase or lowercase, extracting text from the beginning, middle, or end of the text, replacing values, testing whether the text starts or ends with specific values, as well as splitting or combining text.
  • We used variables as placeholders for different values. Looking at the reference docs, you can...
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