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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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

Other types of Decision Nodes

We’ve already created two types of decision nodes – the Decision Table that we used earlier in this chapter and the literal expression we used to generate our greeting in Chapter 3.

But when we were creating our decision node, we had to choose from one of seven types. We’ll work through them in the following list. In some ways, the name decision node can be misleading; often, we will use these types as data preparation nodes to feed into a Decision table:

  • Literal Expressions: These are simple FEEL expressions, broadly similar to a formula you’d enter in Excel. They return a single value.
  • Decision Tables: We have covered these in this chapter. They allow us to group rules in a when … then format.
  • Functions: This allows us to define reusable logic. We could write a function that takes the parameters of a chocolate bar’s weight and the percentage of chocolate, then returns the actual grams of chocolate...