Quick Reference Guides

This guide provides an overview of three primary analytics organizational structures: centralized, balanced (or hybrid), and decentralized. Each structure is dissected to present its characteristics, benefits, and potential drawbacks.

This resource offers a practical, checklist-based approach to applying foundational data and analytics principles, empowering you to handle data responsibly, derive actionable insights, and drive impactful change.

Are you making decisions based on the wrong questions? Many business and data challenges stem from flawed questions that lead to misguided insights and wasted resources. This guide helps you identify common flaws in questioning and how to correct them.

This guide outlines the seven key behaviors executive leaders can model to build trust, curiosity, and accountability around data. Each behavior is practical, repeatable, and designed to embed data thinking into everyday leadership.

This guide is designed to support individuals in making data-informed decisions across key organizational areas. It provides a comprehensive matrix of decision types, relevant data sources, metrics, tools, and techniques to help users quickly identify the essential components for effective and strategic decision-making.

This guide provides a structured framework for categorizing and understanding data within an organization. It helps professionals efficiently identify relevant data types for various purposes, supporting better decision-making and alignment with organizational goals.

This guide helps professionals spot crucial moments to apply data for improved decision-making and process enhancement. It provides practical indicators, examples, and guiding questions to help users recognize data-driven opportunities across various business scenarios.

This checklist is a guide to help creators of visualizations validate their effectiveness and accessibility. It encompasses key principles of design and data representation, ensuring that visualizations are not only visually appealing but also clear, intuitive, and accessible to a diverse audience.

This quick reference guide provides a condensed overview of how to leverage systems thinking concepts, mindsets, and practices to enhance data-driven decision-making.

This guide provides a high-level summary of key insights and recommendations exploring the impacts of data, analytics, and AI on transforming work and skills. It highlights major statistics, trends, and implications regarding the future of work driven by technological advances.

The PROMPT Framework Quick Guide is a handy two-page reference highlighting the key steps and strategies for effective prompt engineering with AI systems.

A practical framework to help you think critically when using AI. Learn how to use, evaluate, question, and reflect on AI outputs with clarity, confidence, and responsibility.

This quick guide provides best practices for responsibly leveraging generative AI to augment human analysis and critical thinking.

Explore different categories of AI applications, their specific use cases, and important ROI considerations to help your organization make informed AI investment decisions.

This guide provides a checklist to follow through each of the 8 stages of data-informed decision-making.

This guide arms you with critical skills to evaluate ad hoc visualizations commonly encountered in media and blogs.

A practical guide to selecting visualizations, with specific recommendations based on data types and goals.

A practical guide on the impact and effectiveness of visual data.

Covers the general benefits of using data visualizations like speed of processing, retention and memory, etc...

This guide provides an overview of the 9 components of data literacy, listing the competencies for each.

This guide walks users through an easy-to-follow classification framework, and offers a streamlined approach to evaluating decisions based on their unique characteristics—such as impact, risk, stakeholder involvement, and complexity.