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The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data
Contrary to popular myth, we do not yet live in the "Information Age." At best, we live the "Data Age," obsessed with the production, collection, storage, dissemination, and monetization of digital data. But data, in and of itself, isn't valuable. Data only becomes valuable when we make sense of it.
We rely on "information professionals" to help us understand data, but most fail in their efforts. Why? Not because they lack intelligence or tools, but mostly because they lack the necessary skills. Most information professionals have been trained primarily in the use of data analysis tools (Tableau, PowerBI, Qlik, SAS, Excel, R, etc.), but even the best tools are only useful in the hands of skilled individuals. Anyone can pick up a hammer and pound a nail, but only skilled carpenters can use a hammer to build a reliable structure. Making sense of data is skilled work, and developing those skills requires study and practice.
Weaving data into understanding involves several distinct but complementary thinking skills. Foremost among them are critical thinking and scientific thinking . Until information professionals develop these capabilities, we will remain in the dark ages of data.
This book is for information professionals, especially those who have been thrust into this important work without having a chance to develop these foundational skills. If you're an information professional and have never been trained to think critically and scientifically with data, this book will get you started. Once on this path, you'll be able to help usher in an Information Age worthy of the name.
We rely on "information professionals" to help us understand data, but most fail in their efforts. Why? Not because they lack intelligence or tools, but mostly because they lack the necessary skills. Most information professionals have been trained primarily in the use of data analysis tools (Tableau, PowerBI, Qlik, SAS, Excel, R, etc.), but even the best tools are only useful in the hands of skilled individuals. Anyone can pick up a hammer and pound a nail, but only skilled carpenters can use a hammer to build a reliable structure. Making sense of data is skilled work, and developing those skills requires study and practice.
Weaving data into understanding involves several distinct but complementary thinking skills. Foremost among them are critical thinking and scientific thinking . Until information professionals develop these capabilities, we will remain in the dark ages of data.
This book is for information professionals, especially those who have been thrust into this important work without having a chance to develop these foundational skills. If you're an information professional and have never been trained to think critically and scientifically with data, this book will get you started. Once on this path, you'll be able to help usher in an Information Age worthy of the name.
142 pages, Paperback
Published May 15, 2019
12 people are currently reading
226 people want to read
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Displaying 1 - 5 of 5 reviews
December 4, 2019
This books feels like "a manifest for craftsmanship when working with data", highlighting the importance of using a proper scientific/intellectual approach and advocating honesty when working with data, so that the right conclusions are drawn.
The author does this mainly by indicating the different aspects of reasoning/thinking that are needed for proper craftsmanship.
All of that made me want to give this book a 5/5. However, after setting the stage with the overview of things, I found that the book didn't dive into details as much as it could have. Therefore, it ended up as a 4/5; which still makes it a recommendation for people that identify themselves as analysts, who want to live by the proper values when working with data.
The author does this mainly by indicating the different aspects of reasoning/thinking that are needed for proper craftsmanship.
All of that made me want to give this book a 5/5. However, after setting the stage with the overview of things, I found that the book didn't dive into details as much as it could have. Therefore, it ended up as a 4/5; which still makes it a recommendation for people that identify themselves as analysts, who want to live by the proper values when working with data.
September 12, 2019
Short simple book with the premise that different types of thinking are crucial to really be able to use data appropriately for decision making. Much less around data tools and how to use them and much more about how to think and ask the right questions to get the value of the book.
September 17, 2019
Highly recommend this 122 page book for anyone involved or interested in data and data analysis.
The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data
by Stephen Few
Excellent review at https://gnfrazier.me/book-review-the-...
The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data
by Stephen Few
Excellent review at https://gnfrazier.me/book-review-the-...
July 12, 2021
People are looking for simple answers. An instruction to use some software to convert data into a dashboard in 3 clicks will be extremely popular. Even if the dashboard will be based on erroneous data. Even if the dashboard will be useful only to get misleading 'insights'. Even if what you do makes no sense at all. People do not care about senses. People are in hurry. They have no time to read philosophy books, they have no time to think, they have no time to sleep. They are looking for an instruction to do their job faster to get a bonus. Good thing - not all people who work with data are looking for quick and simple answers to simple questions. And Stephen Few is asking great questions in this book. Questions with no simple answers.
Do these data make sense? Do our questions about the data make sense? Does our work make sense? Working with data without asking questions about data origin, data quality, context, cause, usefulness makes no sense. Preparing a report in hurry makes no sense. We need time to sleep well, to ask questions, to explore data, to understand context, to ask questions again.
Do not compare this book with other books by Stephen Few. Do not think “it’s a small book about thinking and I can think well without a book, I’ll better buy one of his bigger and more practical books about data visualization”. Just stop for a day, get into a comfortable armchair (in my case it was a hammock I hung in a park), and read this short, but particularly important book. Then start asking questions that have no simple answers. And I will be packing my backpack. The best place to sleep well for me is a hammock in the middle of a forest. And it is important. Because I work with data.
Do these data make sense? Do our questions about the data make sense? Does our work make sense? Working with data without asking questions about data origin, data quality, context, cause, usefulness makes no sense. Preparing a report in hurry makes no sense. We need time to sleep well, to ask questions, to explore data, to understand context, to ask questions again.
Do not compare this book with other books by Stephen Few. Do not think “it’s a small book about thinking and I can think well without a book, I’ll better buy one of his bigger and more practical books about data visualization”. Just stop for a day, get into a comfortable armchair (in my case it was a hammock I hung in a park), and read this short, but particularly important book. Then start asking questions that have no simple answers. And I will be packing my backpack. The best place to sleep well for me is a hammock in the middle of a forest. And it is important. Because I work with data.
November 13, 2021
It's short, but boring book. The author quotes from "Thinking fast and slow" and many other books - I would say at least 10% of the book is quotes.
He has one example - about stroke data for hospitals-which he is using beyond reasonable as well.
He has one example - about stroke data for hospitals-which he is using beyond reasonable as well.
Displaying 1 - 5 of 5 reviews