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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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

Training models in Azure Machine Learning

Since our aim in this chapter is to give a broad introduction, we’re going to train our first naïve Bayes model using Azure ML to give you a gateway into the other tools and techniques offered by Microsoft. Azure ML is not strictly required—the Python notebook will happily run in VS Code online using the method we introduced earlier in the chapter. If you’re following this approach, skip to the Step-by-step training of the ML model section. But since Azure gives additional ML tools aimed at Excel power users, it is worth following the instructions in the next section to get up and running in Azure ML (formerly known as ML Studio).

Setting up Azure Machine Learning

To get started, if your organization doesn’t already have an account, sign up for the free trial at https://azure.microsoft.com/en-us/products/machine-learning/. Microsoft typically offers $200 of credits, with many services free for the first...