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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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

Summary

This chapter gave you another option to access the Scenario Simulation tool, this time using Business Central. Since our method for running Business Central relied on Docker, we took advantage of container technology to explore many different ways of deploying KIE Server images, from locally on our laptop through to scaling a deployment into the cloud. That gives us the confidence that we have many more options to edit and deploy our Business Rules within our organization as the use of decision models grows.

We will return to Business Central in Chapter 12, where we use it as a platform to demonstrate some advanced rule editing techniques. Docker will prove useful in the next chapter, as we use it to host Docker images for machine learning. And we’ll return to Azure, using Machine Learning Studio as a tool to train our models.

This book set out to focus on rules-based decision models within AI. But we would be remiss if we didn’t touch on the other main...