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 Key FeaturesExplore the business rule tools by implementing real-world examples to write sophisticated rulesDiscover how decision services solve current business challenges using AICombine rules with workflows and scripting to deploy a cloud-based production environmentBook Description 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Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets.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. What you will learnUse KIE and Drools decision services to write AI-based business rulesLink Business Rules to Excel using Power Query, Script Lab, Office Script, and VBABuild an end-to-end workflow with Microsoft Power Automate and Forms while integrating it with Excel and KogitoCollaborate on and deploy your decision models using OpenShift, Azure, and GitHubDiscover advanced editing using the graphical Decision Model Notation (DMN) and testing toolsUse Kogito to combine AI solutions with ExcelWho this book is for 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.

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project

This book constitutes the refereed proceedings of the Second International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2005, held in Prague, Czech Republic, in May/June 2005. The 26 revised full papers published together with an invited paper and abstracts of 2 invited talks were carefully reviewed and selected from close to 100 submissions. Methodological and foundational issues from AI , OR, and algorithmics are presented as well as applications to the solution of combinatorial optimization problems in various fields.

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