Book Image

AI and Business Rule Engines for Excel Power Users

By : Paul Browne
Book Image

AI and Business Rule Engines for Excel Power Users

By: Paul Browne

Overview of this book

Microsoft Excel is widely adopted across diverse industries, but Excel Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets. They need a better enterprise-level solution, and this book introduces Business rules combined with the power of AI to tackle the limitations of Excel. This guide will give you a roadmap to link KIE (an industry-standard open-source application) to Microsoft’s business process automation tools, such as Power Automate, Power Query, Office Script, Forms, VBA, Script Lab, and GitHub. You’ll dive into the graphical Decision Modeling standard including decision tables, FEEL expressions, and advanced business rule editing and testing. By the end of the book, you’ll be able to share your business knowledge as graphical models, deploy and execute these models in the cloud (with Azure and OpenShift), link them back to Excel, and then execute them as an end-to-end solution removing human intervention. You’ll be equipped to solve your Excel queries and start using the next generation of Microsoft Office tools.
Table of Contents (22 chapters)
Free Chapter
1
Part 1:The Problem with Excel, and Why Rule-Based AI Can Be the Solution
5
Part 2: Writing Business Rules and Decision Models – with Real-Life Examples
9
Part 3: Extending Excel, Decision Models, and Business Process Automation into a Complete Enterprise Solution
13
Part 4: Next Steps in AI, Machine Learning, and Rule Engines
Appendix A - Introduction to Visual Basic for Applications

What we’ve learned in this book

We started this book in a slightly dark place – we were avid users of Excel, but unsure of how to solve the problems we were encountering. Chapter 1 of this book brought some light; we learned that we were not alone in having these problems and there were rule-based AI tools that might help solve them. Chapter 2 went further, looking at the range of available engines and choosing KIE and Drools as the best available option to work with in Excel.

We got very practical in Chapters 3 and 4 – writing our first decision models and executing them online in KIE Sandbox, before exploring more of the power of the editor, backed up the KIE Services execution tool. We then shared our work in Chapter 5, allowing colleagues to view our rules in the OpenShift cloud and collaborate with us in editing the rules via GitHub.

Chapter 6, 7, and 8 allowed us to use our newly learned decision modeling powers within Excel using a range of options...