Data Literacy in Practice: A complete guide to data literacy and making smarter decisions with data through intelligent actions

"Congratulations to Angelika Klidas and Kevin Hanegan for this reference on how organizations can manage and leverage data & analytics from a cultural aspect. The book details an ideal organizational data journey--especially going beyond simple yet ubiquitous hindsight-only analytics to the promised land of diagnostic, predictive and prescriptive analytics, and how to structure and organize for analytic success. It includes guidance on culture, measuring and managing to success, explaining the importance of data management/quality/governance in business terminology, aligning analytics with organizational objectives, choosing ideal visuals, responsible data handling, and an overall framework for data literacy.The book is a great read and reference, as it includes stories, tools & techniques, illustrations, and frameworks--everything you'd expect and want from such a book. Highly recommended for any and all data & analytics leaders.The major areas the book falls short is in helping data & analytics leaders make the financial and economic business case for managing data as an actual asset, identifying the various ways organizations should be thinking about how to monetize their (and others') data assets, and measuring the potential and realized value of their data assets. The book entirely fails to acknowledge prior work, ideas, and best practices on these increasingly critical topics. Also, it's not all about identifying and solving *problems* as their Data Literacy Competency Framework indicates, but rather organizations should be trained on how to look at data opportunistically as well. And I would have liked to see treatment of the increasingly important topics of data literacy within an AI context and how legal teams should ensure that technology-related contracts should address data-related rights & responsibilities beyond privacy (e.g. sovereignty, residency, localization, etc.)"--Doug Laney, Innovation Fellow, Data & Analytics Strategy, West Monroe, and author of "Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage" and "Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets."

In this comprehensive guide geared towards newcomers to data literacy, the author dissects the key concepts and techniques necessary for making data-driven decisions. As a beginner-friendly text, experienced practitioners may find the content oversimplified. Yet, it is an excellent foundation for those seeking to understand data-driven decision-making more deeply.The book begins by exploring data literacy and its applications in everyday life. It delves into various disciplines and their roles in data and analytics projects. It doesn’t simply focus on the individual, but It also discusses how organizations can develop their data-driven decision-making capabilities simply by building a solid foundation encompassing mission, vision, and strategy. The author also provides valuable insights into various types of analysis, such as descriptive, diagnostic, predictive, and prescriptive, while sharing a real-life example of a successful data-driven team.The book introduces readers to a four-pillar approach supporting an organization's use of data and analytics. It emphasizes the importance of organizational data literacy, data management, data visualization, and education. Using work experience stories and examples, the author illustrates how these elements can help an organization grow during its data literacy journey. This book is highly recommended for those seeking a robust understanding of data and its role in making informed decisions.

"Data Literacy in Practice” is a must-read for anyone interested or involved in data literacy, especially from an organizational point of view. The book is divided into three parts, each designed to help readers better understand the importance of data in their personal and professional lives.The first part of the book is great for people who are just starting to explore what it means to be data literate. The authors break down the basics and introduce readers to the steps needed to understand the data impacting them in everyday life. This section is especially helpful for those who are not involved in working with data.The second part of the book is geared towards people who are more involved in getting an organization to become more data oriented. This section is excellent for those who need to learn how to question data and understand the visualizations and information that is being put out there.Finally, the third part of the book focuses on taking action to get an organization and the people in it more data literate. The authors cover essential skills and competencies that are necessary for success and provide practical guidance for starting and managing data projects. The assessments included in this section can help readers see where they and their organization currently stand, allowing them to take steps to improve.Overall, "Data Literacy in Practice” is an insightful and comprehensive guide to data literacy. It helps readers understand the importance of data and how it impacts their lives and organizations. It is a great read for anyone interested in or involved with data, and I highly recommend it.

Data literacy has become an essential skill for individuals and organizations to succeed in our data-driven world. "Data Literacy in Practice" is a comprehensive guide for anyone looking to improve their understanding of data literacy basics and accelerate their journey to uncovering insights independently. Written by two data literacy pioneers, the book provides practical models, best practices, and real-world examples to help you make your data work for you.The book introduces the four-pillar model that underpins all data and analytics, covering concepts such as measuring data quality, setting up a pragmatic data management environment, choosing the right graphs for your readers, and questioning your insights.

My big complaint is that he introduces lots of terms but doesn't in many, many cases define those terms in a clear and concise way. I have one or more college textbooks which do a much better job.