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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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

A more sophisticated Decision Table

We added a function node to calculate the day of the week our customer was born on. But we still haven’t used that day of the week to recommend a suitable product. Let’s update our previous example (downloadable as 04_Customer_Birth_Day.dmn) to make this happen:

  1. Open the Decision Model, right-click on the Recommended product decision node, and choose the edit icon.
  2. Add Input Clauses (pale blue) so that you have the three input columns, as shown in Figure 4.24. You can do this by right-clicking on an existing input column and choosing Add right.
  3. Double-click on each input clause to set where the data is coming from, as shown in Figure 4.24. Customer.Country of Residence and Customer.Number come directly from our data model. DayCalc(Customer.Date of Birth) calls the function (once) that we created and makes the result available to match against our rules.
  4. We’ve resized some columns and dragged and dropped them...