Individuals, teams, and enterprises that work confidently with data unlock a new realm of possibilities. The resulting agility, growth, and inevitable success have one origin: data literacy.
Data Literacy in Practice is a comprehensive, hands-on guide that builds an understanding of data literacy from the ground up and accelerates the reader's journey to independently uncovering insights with best practices, practical models, and real-world examples.
Co-authored with Angelika Klidas, the book introduces the Four-Pillar Model that underpins all data and analytics work. It walks through concepts like measuring data quality, setting up a pragmatic data management environment, choosing the right charts for the right readers, and questioning the insights you discover. Each chapter pairs theory with practical templates, business case examples, and lessons from working in the field.
This is a book for data analysts, data professionals, and data teams starting or wanting to accelerate their data literacy journey. The skills and mindset you need to work independently with data, paired with the tools and frameworks to start making data work for you today.
The flow of data in daily life, the journey from descriptive to prescriptive analytics, the Four-Pillar Model that underpins all data and analytics work, implementing organizational data literacy, and managing the data environment. The foundational vocabulary and frameworks for everything that follows.
Aligning measurement with organizational goals through proper KPIs. Designing dashboards and reports that actually communicate. Questioning the data with rigor: spotting outliers, separating correlation from causation, recognizing the difference between signal and noise.
Handling data responsibly and ethically. Assessing data literacy maturity at the individual and organizational levels. Managing data and analytics projects: writing the business case, identifying roles, navigating typical project risks, and finishing what you start.
The book's anchoring framework. Four fundamental pillars of an organization's data and analytics capability: organizational data literacy, data management, data and analytics approach, and education. Each pillar gets a chapter of practical guidance, with the model used to diagnose where an organization is strong, where it is weak, and where to invest next.
Lessons drawn from the COVID-19 pandemic and how news headlines mislead. The Oakland A's and Moneyball. Airbnb's filters as a data literacy lesson. Netflix and Spotify's data-driven personalization. Plus practical "intermezzo" sections that show how authors applied these ideas in real organizational settings.
A complete appendix of working templates. Project intake forms. Business case layouts. Financial analysis frameworks. Risk assessment structures. KPI description templates. The supporting infrastructure for putting data literacy into practice, not just understanding it.
Data is more than a commodity in our digital world. It is the ebb and flow of our modern existence. Individuals, teams, and enterprises that work confidently with data unlock a new realm of possibilities. The resultant agility, growth, and inevitable success have one origin: data literacy.
Data Literacy in Practice is a comprehensive guide that will build your understanding of data literacy basics, and accelerate your journey to independently uncovering insights with best practices, practical models, and real-world examples.
By the end of the book, you'll be equipped with a combination of skills and mindsets, along with tools and frameworks, that allow you to find insights and meaning within your data to enable effective and efficient data-informed decision-making.
Kevin works with organizations on enterprise data literacy programs, capability assessments, and learning design. Many engagements are based directly on the framework in this book.