AI and Business Rule Engines for Excel Power Users: Capture and scale your business knowledge into the cloud – with Microsoft 365, Decision Models, and AI tools from IBM and Red Hat

by Paul Browne

A power-packed manual to enhance your decision-making with the application of Business Rules using KIE, Drools, Kogito, MS Excel, Power Automate, Office Script, and MS Forms Purchase of the print or Kindle book includes a free PDF eBook 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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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. This book is for Excel power users, business users, and business analysts looking for a tool to capture their knowledge and deploy it as part of enterprise-grade systems. Working proficiency with MS Excel is required. Basic knowledge of web technologies and scripting would be an added advantage.

386 pages, Paperback

Published March 31, 2023

Reviews

[Matteo Mortari · Rating 5 out of 5]

This book is an excellent guide for both software developers and business analysts seeking to scale the automation of their business knowledge into the cloud. It provides an in-depth analysis of how decision models and semantic rules can be combined with other AI models, to solve some of the inherent limitations of Excel –which is an omnipresent tool in every business and industry sector. The book introduces readers to industry-standard open source Drools rule engine and Kogito, and how these can be linked with many of Microsoft's tools.

The author presents very easy-to-follow examples to teach readers how to author sophisticated decision models, how to develop decision services in order to solve current business challenges using AI (both ML and symbolic AI), and how to combine rules with workflows to deploy a cloud-based solution. The book also covers advanced modeling using the Decision Model and Notation (DMN) open standard and related testing tools.

If you are already familiar with some of the KIE projects, you might be tempted to jump straight reading from Chapter 6 onwards; but my recommendation would be to make sure to revisit the initial chapters nevertheless, especially Chapters 1-2, since they will equip you with important considerations when evaluating the adoption of the powerful techniques presented in this book in your organisation. It is also to be noted that while specific to Microsoft tools, the techniques presented in this book can very likely be analogously applied using other software provider platforms and other hyperscalers.