Data Literacy in Practice

Data Literacy in Practice

A Complete Guide To Data Literacy And Making Smarter Decisions With Data Through Intelligent Actions

When I first started speaking on the topic of data literacy (when I had far fewer grey hairs) it was not yet called data literacy. While my early work used to focus on the adoption of dashboards and data from the technical teams' perspective (i.e. how do the BI and analytics departments speak the language of the business and engage with business stakeholders), over the years it has shifted to include more enablement the end consumers of data through change management processes and adoption methodologies. Indeed, you probably know me for building board game approaches to data adoption and dashboard design for non-technical people.

With that in mind, when I first opened the newly released book "Data Literacy in Practice" by Angelika Klidas and Kevin Hanegan, published by Packt, I can honestly say I was not expecting the breadth of topics covered in the book. From the high-level perspective of organizational data literacy and strategic approaches to enabling it on a company-wide scale right down to individual-level competencies and frameworks. There is even a chapter on assessing your data literacy maturity.

Especially close to my heart were the topics of KPI design and crafting impactful dashboards. You can tell an immense amount of work went into this book and it shows.

I'm happy to recommend this book, it has a wealth of information on the topic for professionals, regardless of how far along they are on their data literacy journey.

~ Nicholas Kelly, Author of Delivering Data Analytics: A Step-By-Step Guide to Driving Adoption of Business Intelligence from Planning to Launch

Turning Data into Wisdom

Data Literacy in Practice

How We Can Collaborate with Data to Change Ourselves, Our Organizations, and Even the World

Kevin Hanegan presents a six-phase, twelve-step process for gathering, interpreting, and applying data for decision-making. Hanegan makes what might seem to be a dry and imposing subject interesting and easy to understand. One does not need to be a mathematician to follow the process Hanegan describes. He provides examples throughout the book and provides a chapter with case studies to illustrate how the processes and tools are applied. He takes a multidisciplinary approach to data analysis. An entire chapter is devoted to explaining relevant tools, frameworks, and models. This is a useful book for anyone wanting to make data-informed decisions in a professional or personal context.

~ Mitchell Ray