Book Image

AI and Business Rule Engines for Excel Power Users

By : Paul Browne (GBP), PORCELLI
Book Image

AI and Business Rule Engines for Excel Power Users

By: Paul Browne (GBP), PORCELLI

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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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

Who this book is for

While there are a billion people who will benefit from reading this book, it is written with three key groups in mind:

  • Excel Power users who have reached the limit of Microsoft Office 365 and are wondering what's next, especially as AI tools are becoming more and more powerful.
  • Business analysts and knowledge workers looking for a tool to capture their knowledge and deploy it as part of enterprise-grade systems.
  • People who are joining an existing rules, AI, or workflow project using decision models, as many of the tools will already be set up; they will find the introduction to DMN and FEEL particularly useful.

Other people will also find the book useful, such as machine learning experts looking for a rules-based safety net for their predictive models. The book will also have value for developers who are looking for a more structured approach to implementing AI and business logic, no matter what language they use.