Augmented Analytics

Augmented Analytics isn’t just another book on data and analytics; it’s a holistic resource for reimagining the way your entire organization interacts with information to become insight-driven.

Moving beyond traditional, limited ways of making sense of data, Augmented Analytics provides a dynamic, actionable strategy for improving your organization’s analytical capabilities. With this book, you can infuse your workflows with intelligent automation and modern artificial intelligence, empowering more team members to make better decisions.

You’ll find more in these pages than just how to add another forecast to your dashboard; you’ll discover a complete approach to achieving analytical excellence in your organization.

You’ll explore:

• Key elements and building blocks of augmented analytics, including its benefits, potential challenges, and relevance in today’s business landscape
• Best practices for preparing and implementing augmented analytics in your organization, including analytics roles, workflows, mindsets, tool sets, and skill sets
• Best practices for data enablement, liberalization, trust, and accessibility
• How to apply a use-case approach to drive business value and use augmented analytics as an enabler, with selected case studies

This book provide a clear, actionable path to accelerate your journey to analytical excellence.

Who Should Read This Book?

This book covers many aspects, both methodological and technical, of the broad topic of analytics transformation. The methodological topics are particularly foundational for understanding analytics maturity while the technical topics help you increase that maturity.

The book is especially valuable for experienced analysts and for people in strategic and managerial positions who are responsible for some facet of an analytical or digital transformation. Engineers and other roles concerned with implementing and integrating analytics solutions will, however, appreciate the technical concepts and frameworks we provide to help start enhancing workflows in your organization, complete with a minimum viable product (MVP).

In summary, this book is for anyone who understands that, while you can separate analytics into its technological, methodological, and business components, you can make use of them effectively only when you have a comprehensive perspective.

Learning Objectives

By the end of this book, you will understand the following:

• The importance of aligning technological advances with dynamic business strategies and organizational processes
• The critical components of an analytics transformation and how they relate to overall business strategy
• How augmented analytics bridges the gap between traditional analytics environments and insight-driven decision making
• The fundamental roles of the organization’s culture, skills, and mindsets as prerequisites for successfully adopting augmented analytics
• The relevance of analytical roles and a holistic use-case approach
• The limitations of traditional approaches to analytics
• How augmentation can move your organization forward and make workflows more efficient
• The challenges of implementing augmented analytics
• How to introduce augmentation into the enterprise infrastructure
• How combining analytics with software-engineering techniques can kick-start your first analytics-augmentation MVPs

You’ll also be able to:

• Assess your organization’s current analytical maturity and identify areas for improvement
• Evaluate and adapt your analytics strategies in response to evolving business needs and market trends
• Develop a strategic roadmap for analytics transformation tailored to your organization’s unique needs and goals
• Address the technological, organizational, and cultural challenges associated with analytics transformation
• Develop methodological and technical concepts for your individual augmentations
• Implement augmented analytics infrastructures and integrate them into your business processes

Table of Contents

Chapter 1. The Business Transformation

Chapter 2. The Analytics Problem

Chapter 3. Understanding Augmented Analytics

Chapter 4. Preparing People and the Organization for Augmented Analytics

Chapter 5. Augmented Workflows

Chapter 6. Augmented Frames

Chapter 7. Applied Examples

About the Author

Tobias Zwingmann is a leading expert, speaker, and author on artificial intelligence. In his role as managing partner of the German AI advisory firm RAPYD.AI, he helps B2B companies around the world innovate and grow their businesses with AI and machine learning. Prior to cofounding RAPYD.AI, he worked for more than 10 years in a corporate setting where his responsibilities included creating a company-wide data strategy and building out data science use cases. He also authored the book AI-Powered Business Intelligence (O’Reilly).

Tobias Zwingmann is an experienced Senior Data Scientist and Managing Partner at RAPYD.AI, a Germany-based AI startup focused on providing easy access to world-class AI services. His mission is to help companies adopt machine learning and AI solutions faster while creating meaningful business impact and reducing the risk of project failure. Before founding RAPYD.AI, he has worked for more than 10 years in a corporate setting where his responsibilities included creating a company-wide data strategy and building out data science use cases. He is author of the book AI-Powered Business Intelligence (O’Reilly).